All | Articles | Conference Proceedings

2019

  1. Assessment of Simplifications to a Pseudo–2D Electrochemical Model of Li-ion Batteries Kong, X.R., Wetton, B., and Gopaluni, R.B. 2019. In Proceedings of DYCOPS Conference, , 946-951. [Abstract] [PDF]
  2. Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction Wang, K., Gopaluni, R.B., Chen, J., and Song, Z. 2019. IEEE Transactions on Industrial Informatics, To Appear , . [Abstract] [PDF] [DOI]
  3. Identification of Symmetric Noncausal Processes Lu, Q., Loewen, P.D., Gopaluni, R.B., Forbes, M.G., Backstrom, J.U., Dumont, G.A., and Davies, M.S. 2019. Automatica, 103 , 515-530. [Abstract] [PDF]
  4. Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes Wang, K., Forbes, M.G., Gopaluni, R.B., Chen, J., and Song, Z. 2019. IEEE Access, 7 , 22554-22565. [Abstract] [PDF] [DOI]
  5. Data-Driven Dynamic Modeling and Online Monitoring for Multiphase and Multimode Batch Processes with Uneven Batch Durations Wang, K., Forbes, L, Chen, J., Song, Z., and Gopaluni, R.B. 2019. Industrial and Engineering Chemistry Research (Prof. Dominique Bonvin - Festschrift), 7 , 22554-22565. [Abstract] [PDF] [DOI]
  6. Machine Direction Adaptive Control on a Paper Machine Rippon, L. D., Lu, Q., Forbes, M.G., Gopaluni, R.B., Loewen, P.D., and Backstrom, J.U. 2019. Industrial and Engineering Chemistry Research (Prof. Sirish Shah - Festschrift), 7 , 22554-22565. [Abstract] [PDF] [DOI]
  7. Univariate model-based deadband alarm design for nonlinear processes Tulsyan, A., and Gopaluni, R.B. 2019. Industrial and Engineering Chemistry Research (Prof. Sirish Shah - Festschrift), To Appear , . [Abstract] [PDF] [DOI]
  8. Development and Characterization of a Non- Intrusive Magnetic Sensor to Measure Wear in Centrifugal Pumps Bohn, B., Khoie, R., Gopaluni, R.B., Olson, J.A., and Stoeber, B. 2019. IEEE Sensors, To Appear , . [Abstract] [PDF] [DOI]
  9. Towards Self-Driving Processes: A Deep Reinforcement Learning Approach to Control Speilberg, S., Tulsyan, A., Lawrence, N.P., Loewen, P.D., and Gopaluni, R.B. 2019. AIChE Journal, To Appear , . [Abstract] [PDF] [DOI]
  10. Design and Application of a Database-Driven PID Controller with Data-Driven Updating Algorithm Wakitani, S., Yamamoto, T., and Gopaluni, R.B. 2019. Industrial and Engineering Chemistry Research, To Appear , . [Abstract] [PDF] [DOI]
  11. An economic model predictive control framework for mechanical pulping processes Tian, H., Lu, Q., Gopaluni, R.B., Zavala, V.M., and Olson, J.A. 2019. Control Engineering Practice, 85 , 100-109. [Abstract] [PDF] [DOI]

2018

  1. State of Health Estimation for Lithium-Ion Batteries Kong, X., Bonakdarpour, A., Wetton, B.T., Wilkinson, D.P., and Gopaluni, R.B. 2018. In Proceedings of ADCHEM Conference, 51 , 661-665. [Abstract] [PDF] [DOI]
  2. Design and Assessment of Delay Timer Alarm Systems for Nonlinear Chemical Processes Tulsyan, A., Alrowaie, F., and Gopaluni, R.B. 2018. AIChE Journal, 64((1) , 77-90. [Abstract] [PDF] [DOI]
  3. Application of neural networks for optimal-setpoint design and MPC control in biological wastewater treatment Sadeghassadi, M., Macnab, C.J.B., Gopaluni, R.B., and Westwick, D. 2018. Computers & Chemical Engineering, 115 , 150–160. [Abstract] [PDF] [DOI]
  4. Locality Preserving Discriminative Canonical Variate Analysis for Fault Diagnosis Lu, Q., Jiang, B., Gopaluni, R.B., Loewen, P.D., and Braatz, R.D. 2018. Computers & Chemical Engineering, 117 , 309-319. [Abstract] [PDF] [DOI]
  5. Sparse canonical variate analysis approach for process monitoring Lu, Q., Jiang, B., Gopaluni, R.B., Loewen, P.D., and Braatz, R.D. 2018. Journal of Process Control, 71 , 90-102. [Abstract] [PDF] [DOI]
  6. Pattern and Knowledge Extraction using Process Data Analytics: A Tutorial Tsai, Y., Lu, Q., Rippon, L., Lim, S., Tulsyan, A., and Gopaluni, R.B. 2018. In Proceedings of ADCHEM Conference, 51 , 13-18. [Abstract] [PDF] [DOI]
  7. A Deep Learning Architecture for Predictive Control Spielberg, S., Tulsyan, A., Gopaluni, R.B., and Loewen, P.D. 2018. In Proceedings of ADCHEM Conference, Shenyang, China, 51 , 512-517. [Abstract] [PDF] [DOI]
  8. An Efficient Model Based Control Algorithm for the Determination of an Optimal Control Policy for a Constrained Stochastic Linear System Prakash, J., Zamar, D., Gopaluni, R.B., and Kwok, E. 2018. In Proceedings of ADCHEM Conference, 51 , 584-589. [Abstract] [PDF] [DOI]
  9. A switching strategy for adaptive state estimation Tulsyan, A., Khare, S., Huang, B., Gopaluni, R.B., and Forbes, F.J. 2018. Signal Processing, 143 , 371-380. [Abstract] [PDF] [DOI]

2017

  1. A Constrained k-means and Nearest Neighbor Approach for Route Optimization: With an application to the Bale Collection Zamar, D., Gopaluni, R.B., and Sokhansanj, S. 2017. In Proceedings of IFAC World Congress, , 12125-12130. [Abstract] [PDF] [Presentation]
  2. Model-Plant Mismatch Detection with Support Vector Machines Lu, Q., Gopaluni, R.B., Forbes, M.G., Loewen, P.D., Backstrom, J.U., and Dumont, G.A. 2017. In Proceedings of IFAC World Congress, , 7993-7998. [Abstract] [PDF]
  3. Noncausal Modeling and Closed-Loop Optimal Input Design for Cross-Directional Processes of Paper Machines Lu, Q., Gopaluni, R.B., Forbes, M.G., Loewen, P.D., Backstrom, J.U., and Dumont, G.A. 2017. In Proceedings of American Control Conference, , 2837-2842. [Abstract] [PDF] [Presentation]
  4. Deep Reinforcement Learning Approaches for Process Control Spielberg, S.P., Gopaluni, R.B., and Loewen, P.D. 2017. In Proceedings of ADCONIP, , 201-206. [Abstract] [PDF]
  5. Performance Assessment of Cross-Directional Control for Paper Machines Lu, Q., Forbes, M.G., Gopaluni, R.B., Loewen, P.D., Backström, J.U., and Dumont, G.A. 2017. IEEE Transactions on Control Systems Technology, 25 (1), 208–221. [Abstract] [PDF] [DOI]
  6. A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty Zamar, D.S., Gopaluni, R.B., Sokhansanj, S., and Newlands, N.K. 2017. Computers & Chemical Engineering, 97 , 114–123. [Abstract] [PDF] [DOI]
  7. Optimization of sawmill residues collection for bioenergy production Zamar, D.S., Gopaluni, R.B., and Sokhansanj, S. 2017. Applied Energy, 202 , 487–495. [Abstract] [PDF] [DOI]

2016

  1. Particle filtering without tears: A primer for beginners Tulsyan, Aditya, Gopaluni, R Bhushan, and Khare, Swanand R 2016. Computers & Chemical Engineering, 95 , 130–145. [Abstract] [PDF] [Presentation] [Code]
  2. Simple Self-Administered Method for Assessing Insulin Sensitivity in Diabetic Patients Barazandegan, M., Ekram, F., Kwok, E., and Gopaluni, R.B. 2016. Journal of Medical and Biological Engineering, 36 (2), 197–205. [Abstract] [PDF] [DOI]
  3. LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control Torchio, M., Magni, L., Gopaluni, R.B., Braatz, R.D., and Raimondo, D.M. 2016. Journal of The Electrochemical Society, 163 (7), A1192–A1205. [Abstract] [PDF] [DOI] [Code]
  4. Regularized maximum likelihood estimation of sparse stochastic monomolecular biochemical reaction networks Jang, Hong, Kim, Kwang-Ki K, Braatz, Richard D, Gopaluni, R Bhushan, and Lee, Jay H 2016. Computers & Chemical Engineering, 90 , 111–120. [Abstract] [PDF] [Presentation] [Code]
  5. Economic Optimization of Sawmill Residues Collection for Bioenergy Conversion Zamar, David S, Gopaluni, Bhushan, Sokhansanj, Shahab, and Ebadian, Mahmood 2016. IFAC-PapersOnLine, 49 (7), 857–862. [Abstract] [PDF] [Presentation] [Code]
  6. Model-based detection of organ dysfunction and faults in insulin infusion devices for type 2 diabetic patients Barazandegan, M, Kwok, KE, and Gopaluni, RB 2016. In American Control Conference (ACC), 2016, , 3994–3999.
  7. Economic nonlinear model predictive control for mechanical pulping processes Tian, Hui, Lu, Qiugang, Gopaluni, R Bhushan, Zavala, Victor M, and Olson, James A 2016. In American Control Conference (ACC), 2016, , 1796–1801.
  8. Robust model-based delay timer alarm for non-linear processes Tulsyan, Aditya, and Gopaluni, R Bhushan 2016. In American Control Conference (ACC), 2016, , 2989–2994.
  9. Multiobjective economic model predictive control of mechanical pulping processes Tian, Hui, Lu, Qiugang, Gopaluni, R Bhushan, and Zavala, Victor M 2016. In Decision and Control (CDC), 2016 IEEE 55th Conference on, , 4040–4045.
  10. State-of-charge estimation in lithium-ion batteries: A particle filter approach Tulsyan, Aditya, Tsai, Yiting, Gopaluni, R Bhushan, and Braatz, Richard D 2016. Journal of Power Sources, 331 , 208–223. [Abstract] [PDF] [Presentation] [Code]
  11. A comprehensive compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects Vahidi, O., Kwok, K.E., Gopaluni, R.B., and Knop, F.K. 2016. Medical & biological engineering & computing, 54 (9), 1383–1398. [Abstract] [PDF] [DOI]

2015

  1. A magnetic sensor to measure wear in centrifugal pumps Khoie, Ramin, Gopaluni, Bhushan, Olson, James A, and Stoeber, Boris 2015. In SENSORS, 2015 IEEE, , 1–4.
  2. Detection of abnormalities in type II diabetic patients using particle filters Vahidi, Omid, Gopaluni, R Bhushan, and Kwok, Ezra 2015. Journal of Medical and Biological Engineering, 35 (2), 188–201. [Abstract] [PDF] [Presentation] [Code]
  3. Impact of model plant mismatch on performance of control systems: An application to paper machine control Yousefi, M, Gopaluni, RB, Loewen, PD, Forbes, MG, Dumont, GA, and Backstrom, J 2015. Control Engineering Practice, 43 , 59–68. [Abstract] [PDF] [Presentation] [Code]
  4. Detecting model-plant mismatch without external excitation Yousefi, Mahdi, Lu, Qiugang, Gopaluni, R Bhushan, Loewen, Philip D, Forbes, Michael G, Dumont, Guy Albert, and Backstrom, J 2015. In American Control Conference (ACC), 2015, , 4976–4981.
  5. Cross-directional controller performance monitoring for paper machines Lu, Qiugang, Rippon, Lee D, Gopaluni, R Bhushan, Forbes, Michael G, Loewen, Philip D, Backstrom, Johan, and Dumont, Guy A 2015. In American Control Conference (ACC), 2015, , 4970–4975.
  6. Real-time model predictive control for the optimal charging of a lithium-ion battery Torchio, Marcello, Wolff, Nicolas A, Raimondo, Davide M, Magni, Lalo, Krewer, Ulrike, Gopaluni, R Bushan, Paulson, Joel A, and Braatz, Richard D 2015. In American Control Conference (ACC), 2015, , 4536–4541.
  7. A Novel Algorithm for Model-Plant Mismatch Detection for Model Predictive Controllers Tsai, Yiting, Gopaluni, RB, Marshman, D, and Chmelyk, T 2015. IFAC-PapersOnLine, 48 (8), 746–752. [Abstract] [PDF] [Presentation] [Code]
  8. Overload Detection in Semi-Autogenous Grinding: A Nonlinear Process Monitoring Approach McClure, KS, and Gopaluni, RB 2015. IFAC-PapersOnLine, 48 (8), 960–965. [Abstract] [PDF] [Presentation] [Code]
  9. Model predictive control in industry: Challenges and opportunities Forbes, Michael G, Patwardhan, Rohit S, Hamadah, Hamza, and Gopaluni, R Bhushan 2015. IFAC-PapersOnLine, 48 (8), 531–538. [Abstract] [PDF] [Presentation] [Code]
  10. Robust Optimization of Competing Biomass Supply Chains Under Feedstock Uncertainty Zamar, David S, Gopaluni, Bhushan, Sokhansanj, Shahab, and Newlands, Nathaniel K 2015. IFAC-PapersOnLine, 48 (8), 1222–1227. [Abstract] [PDF] [Presentation] [Code]
  11. Moving-Horizon Predictive Input Design for Closed-Loop Identification Yousefi, M, Rippon, LD, Forbes, MG, Gopaluni, RB, Loewen, PD, Dumont, GA, and Backstrom, J 2015. IFAC-PapersOnLine, 48 (8), 135–140. [Abstract] [PDF] [Presentation] [Code]
  12. Evaluation of treatment regimens for blood glucose regulation in type II diabetes using pharmacokinetic-pharmacodynamic modeling Ekram, Fatemeh, Barazandegan, Melissa, Kwok, Ezra, and Gopaluni, Bhushan 2015. In Control Conference (CCC), 2015 34th Chinese, , 8519–8524.
  13. Assessment of type II diabetes mellitus using irregularly sampled measurements with missing data Barazandegan, Melissa, Ekram, Fatemeh, Kwok, Ezra, Gopaluni, Bhushan, and Tulsyan, Aditya 2015. Bioprocess and biosystems engineering, 38 (4), 615–629. [Abstract] [PDF] [Presentation] [Code]

2014

  1. SELF-ASSESSMENT OF INSULIN SENSITIVITY Barazandegan, M, Ekram, F, Kwok, KE, and Gopaluni, RB 2014. SELF, ,
  2. Performance assessment, diagnosis, and optimal selection of non-linear state filters Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2014. Journal of Process Control, 24 (2), 460–478. [Abstract] [PDF] [Presentation] [Code]
  3. Fault Isolation based on General Observer Scheme in Stochastic Non-linear State-Space Models Using Particle Filters Alrowaie, F, Kwok, KE, and Gopaluni, RB 2014. ADCONP, ,
  4. A moving horizon approach to input design for closed loop identification Patwardhan, Rohit S, and Goapluni, R Bhushan 2014. Journal of Process Control, 24 (3), 188–202. [Abstract] [PDF] [Presentation] [Code]
  5. Sparse identification in chemical master equations for monomolecular reaction networks Kim, Kwang-Ki K, Jang, Hong, Gopaluni, R Bhushan, Lee, Jay H, and Braatz, Richard D 2014. In American Control Conference (ACC), 2014, , 3698–3703.
  6. Sensitivity of controller performance indices to model-plant mismatch: An application to paper machine control Yousefi, Mahdi, Forbes, Michael G, Gopaluni, R Bhushan, Dumont, Guy Albert, Backstrom, J, and Malhotra, A 2014. In American Control Conference (ACC), 2014, , 3506–3511.
  7. Increased CHO cell fed-batch monoclonal antibody production using the autophagy inhibitor 3-MA or gradually increasing osmolality Nasseri, S Soroush, Ghaffari, Navid, Braasch, Katrin, Jardon, Mario A, Butler, Michael, Kennard, Malcolm, Gopaluni, Bhushan, and Piret, James M 2014. Biochemical Engineering Journal, 91 , 37–45. [Abstract] [PDF] [Presentation] [Code]
  8. Sensitivity of mimo controller performance to model-plant mismatch, with applications to paper machine control Yousefi, Mahdi, Forbes, Michael G, Gopaluni, R Bhushan, Loewen, Philip D, Dumont, Guy Albert, and Backstrom, J 2014. In Control Applications (CCA), 2014 IEEE Conference on, , 204–209.
  9. Alarm design for nonlinear stochastic systems Alrowaie, F, Gopaluni, RB, and Kwok, KE 2014. In Intelligent Control and Automation (WCICA), 2014 11th World Congress on, , 473–479.
  10. Robust level control of a dry-surge ore pile McClure, Kenneth Scott, Nagamune, Ryozo, Marshman, Devin, Chmelyk, Terrance, and Gopaluni, Bhushan 2014. The Canadian Journal of Chemical Engineering, 92 (3), 486–495.

2013

  1. A moving horizon approach to multivariable input design in general linear systems with constraints Patwardhan, RS, and Gopaluni, RB 2013. IFAC Proceedings Volumes, 46 (32), 577–582. [Abstract] [PDF] [Presentation] [Code]
  2. Use of Molecular Dynamics for the Refinement of an Electrostatic Model for the In Silico Design of a Polymer Antidote for the Anticoagulant Fondaparinux Cajiao, Adriana, Kwok, Ezra, Gopaluni, Bhushan, and Kizhakkedathu, Jayachandran N 2013. Journal of medical engineering, 2013 , [Abstract] [PDF] [Presentation] [Code]
  3. A particle filter approach to approximate posterior Cramér-Rao lower bound: The case of hidden states Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. IEEE Transactions on Aerospace and Electronic Systems, 49 (4), 2478–2495. [Abstract] [PDF] [Presentation] [Code]
  4. On-line Bayesian parameter estimation in general non-linear state-space models: a tutorial and new results Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. arXiv preprint arXiv:1307.3490, ,
  5. Input design for Bayesian identification of non-linear state-space models Tulsyan, Aditya, Khare, Swanand R, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. arXiv preprint arXiv:1307.6258, ,
  6. Error analysis in Bayesian identification of non-linear state-space models Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. arXiv preprint arXiv:1307.6254, ,
  7. Constrained dual ensemble Kalman filter for state and parameter estimation Bavdekar, Vinay A, Prakash, Jagdeesan, Shah, Sirish L, and Gopaluni, R Bhushan 2013. In American Control Conference (ACC), 2013, , 3093–3098.
  8. Optimal control and state estimation of lithium-ion batteries using reformulated models Suthar, Bharatkumar, Ramadesigan, Venkatasailanathan, Northrop, Paul WC, Gopaluni, Bhushan, Santhanagopalan, Shriram, Braatz, Richard D, and Subramanian, Venkat R 2013. In American Control Conference (ACC), 2013, , 5350–5355.
  9. Nonlinear process monitoring using supervised locally linear embedding projection McClure, Kenneth S, Gopaluni, R Bhushan, Chmelyk, Terrance, Marshman, Devin, and Shah, Sirish L 2013. Industrial & Engineering Chemistry Research, 53 (13), 5205–5216. [Abstract] [PDF] [Presentation] [Code]
  10. Bayesian identification of non-linear state-space models: Part II-Error Analysis Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. IFAC Proceedings Volumes, 46 (32), 631–636. [Abstract] [PDF] [Presentation] [Code]
  11. Bayesian identification of non-linear state-space models: Part I-Input design Tulsyan, Aditya, Khare, Swanand R, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. IFAC Proceedings Volumes, 46 (32), 774–779. [Abstract] [PDF] [Presentation] [Code]
  12. Evaluation of adaptive extended Kalman filter algorithms for state estimation in presence of model-plant mismatch Bavdekar, Vinay A, Gopaluni, R Bhushan, and Shah, Sirish L 2013. IFAC Proceedings Volumes, 46 (32), 184–189. [Abstract] [PDF] [Presentation] [Code]
  13. State of charge estimation in Li-ion batteries using an isothermal pseudo two-dimensional model Gopaluni, R Bhushan, and Braatz, Richard D 2013. IFAC Proceedings Volumes, 46 (32), 135–140. [Abstract] [PDF] [Presentation] [Code]
  14. A Comparison of Moving Horizon and Bayesian State Estimators with an Application to a pH Process Bavdekar, Vinay A, Gopaluni, R Bhushan, and Shah, Sirish L 2013. IFAC Proceedings Volumes, 46 (32), 160–165. [Abstract] [PDF] [Presentation] [Code]
  15. On simultaneous on-line state and parameter estimation in non-linear state-space models Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. Journal of Process Control, 23 (4), 516–526. [Abstract] [PDF] [Presentation] [Code]

2012

  1. Predicting binding affinities of a novel polymer for the neutralization of fondaparinux and Cajiao, Adriana 2012. ,
  2. A feedback glucose control strategy for type II diabetes mellitus based on fuzzy logic Ekram, F, Sun, L, Vahidi, O, Kwok, E, and Gopaluni, RB 2012. The Canadian Journal of Chemical Engineering, 90 (6), 1411–1417. [Abstract] [PDF] [Presentation] [Code]
  3. Fault detection and isolation in stochastic non-linear state-space models using particle filters Alrowaie, F, Gopaluni, RB, and Kwok, KE 2012. Control Engineering Practice, 20 (10), 1016–1032. [Abstract] [PDF] [Presentation] [Code]
  4. Performance assessment of nonlinear state filters Tulsyan, Aditya, Huang, Biao, Gopaluni, RB, and Forbes, J Fraser 2012. IFAC Proceedings Volumes, 45 (15), 371–376. [Abstract] [PDF] [Presentation] [Code]
  5. Nonlinear Bayesian state estimation: A review of recent developments Patwardhan, Sachin C, Narasimhan, Shankar, Jagadeesan, Prakash, Gopaluni, Bhushan, and L Shah, Sirish 2012. Control Engineering Practice, 20 (10), 933–953. [Abstract] [PDF] [Presentation] [Code]
  6. Editorial: 4th Symposium on Advanced Control of Industrial Processes (ADCONIP) Gudi, Ravi, Gopaluni, Bhushan, and Huang, Biao 2012. Control Engineering Practice, 20 (10), 931–932. [Abstract] [PDF] [Presentation] [Code]
  7. Parameter estimation in models with hidden variables: An application to a biotech process Jang, Seunghee S, Hoz, Hector, Ben-zvi, Amos, McCaffrey, William C, and Gopaluni, R Bhushan 2012. The Canadian Journal of Chemical Engineering, 90 (3), 690–702. [Abstract] [PDF] [Presentation] [Code]
  8. A Receding Horizon Approach to Input Design for Closed Loop Identification Patwardhan, Rohit S, and Gopaluni, R Bhushan 2012. , [Abstract] [PDF] [Presentation] [Code]

2011

  1. Reconstructing Paper Machine Sheet Process Data Variation Using Compressive Sensing Davies, Michael, Gopaluni, Bhushan, Loewen, Philip, Towfighi, Parisa, and Dumont, Guy 2011. IFAC Proceedings Volumes, 44 (1), 4266–4271. [Abstract] [PDF] [Presentation] [Code]
  2. Detection of organ dysfunction in type II diabetic patients Vahidi, O, Gopaluni, RB, and Kwok, KE 2011. In American Control Conference (ACC), 2011, , 4769–4774.
  3. Characterization of gas–solid fluidization: A comparative study of acoustic and pressure signals Li, Yan-qin, Grace, John R, Gopaluni, R Bhushan, Bi, Hsiaotao, Lim, C Jim, and Ellis, Naoko 2011. Powder technology, 214 (2), 200–210. [Abstract] [PDF] [Presentation] [Code]
  4. An algorithm for fault detection in stochastic non-linear state-space models using particle filters Alrowaie, F, Kwok, KE, and Gopaluni, RB 2011. In Advanced Control of Industrial Processes (ADCONIP), 2011 International Symposium on, , 60–65.
  5. Parameter estimation in nonlinear chemical and biological processes with unmeasured variables from small data sets Jang, SS, and Gopaluni, RB 2011. Chemical Engineering Science, 66 (12), 2774–2787. [Abstract] [PDF] [Presentation] [Code]
  6. Nonlinear bayesian state estimation: Review and recent trends Prakash, J, Gopaluni, RB, Patwardhan, Sachin C, Narasimhan, Shankar, and Shah, Sirish L 2011. In Advanced Control of Industrial Processes (ADCONIP), 2011 International Symposium on, , 450–455.
  7. Input Design for Nonlinear Stochastic Dynamic Systems-A Particle Filter Approach Gopaluni, R Bhushan, Schön, Thomas B, and Wills, Adrian G 2011. In IFAC World Congress, 18 (1), 13191–13196.
  8. Pharmacokinetic-Pharmacodynamic Modeling of Metformin for the Treatment of Type II Diabetes Mellitus Sun, Lin, Kwok, Ezra, Gopaluni, Bhushan, and Vahidi, Omid 2011. The Open Biomedical Engineering Journal, 5 , 1. [Abstract] [PDF] [Presentation] [Code]
  9. Reconstructing Variation in a Sheet of Paper Using Compressive Sensing Towfighi, Parisa, Dumont, Guy, Davies, Michael S, Gopaluni, Bhushan, and Loewen, Philip D 2011. In Proceedings of IFAC World Congress, 18 (1), 4266–4271.
  10. In Silico Design of Polymeric Antidote for Anticoagulant Fondaparinux Cajiao, Adriana, Gopaluni, Bhushan, Kwok, Ezra, and Kizhakkedathu, Jayachandran N 2011. Journal of Medical and Biological Engineering, 31 (2), 129–134. [Abstract] [PDF] [Presentation] [Code]
  11. A Feedback Glucose Control Strategy for Type II Diabetes Mellitus Sun, Lin, Kwok, Ezra, Gopaluni, Bhushan, and Vahidi, Omid 2011. In Advanced Control of Industrial Processes (ADCONIP), 2011 International Symposium on, , 349–352.
  12. Developing a physiological model for type II diabetes mellitus Vahidi, O, Kwok, KE, Gopaluni, RB, and Sun, L 2011. Biochemical Engineering Journal, 55 (1), 7–16. [Abstract] [PDF] [Presentation] [Code]

2010

  1. A comparison of simultaneous state and parameter estimation schemes for a continuous fermentor reactor Chitralekha, Saneej B, Prakash, J, Raghavan, H, Gopaluni, RB, and Shah, Sirish L 2010. Journal of Process Control, 20 (8), 934–943. [Abstract] [PDF] [Presentation] [Code]
  2. Nonlinear system identification under missing observations: The case of unknown model structure and Gopaluni, R Bhushan 2010. Journal of Process Control, 20 (3), 314–324. [Abstract] [PDF] [Presentation] [Code]
  3. Energy optimization in a pulp and paper mill cogeneration facility Marshman, DJ, Chmelyk, T, Sidhu, MS, Gopaluni, RB, and Dumont, GA 2010. Applied Energy, 87 (11), 3514–3525. [Abstract] [PDF] [Presentation] [Code]
  4. Economic performance assessment with optimized LQG benchmarking in MIMO systems Marshman, Devin James, Chmelyk, Terrance, Sidhu, MS, Gopaluni, Ratna Bhushan, and Dumont, GA 2010. IFAC Proceedings Volumes, 43 (5), 769–774. [Abstract] [PDF] [Presentation] [Code]
  5. Development of a physiological model forpatients with type 2 diabetes mellitus Vahidi, O, Kwok, KE, Gopaluni, RB, and Sun, L 2010. In American Control Conference (ACC), 2010, , 2027–2032.
  6. Special series of articles on process control Gopaluni, RB, and Duchesne, C 2010. The Canadian Journal of Chemical Engineering, 88 (5), 695–695. [Abstract] [PDF] [Presentation] [Code]
  7. Nonlinear System Identification from Small Data Sets Gopaluni, R Bhushan, and Marshman, Devin 2010. IFAC Proceedings Volumes, 43 (5), 589–594. [Abstract] [PDF] [Presentation] [Code]

2009

  1. Comparison of expectation-maximization based parameter estimation using particle filter, unscented and extended Kalman filtering techniques Chitralekha, Saneej, Prakash, Jagadeesan, Raghavan, Harigopal, Gopaluni, Ratna Bhushan, and Shah, Sirish 2009. In IFAC Conference on System Identification, 15 (1), 804–809.
  2. Identification of nonlinear state-space models: the case of unknown model structure and Gopaluni, R Bhushan 2009. IFAC Proceedings Volumes, 42 (11), 470–475. [Abstract] [PDF] [Presentation] [Code]
  3. A note on separating machine direction and cross machine data on a paper machine Gopaluni, RB, Davies, MS, Loewen, PD, Stewart, GE, and Dumont, GA 2009. NORDIC Pulp & Paper Research Journal, 24 (3), 273–277.
  4. Parameter Estimation of Stochastic Nonlinear Dynamic Processes using Multiple Experimental Data Sets and Jang, Seunghee Shelly 2009. ,
  5. Particle filter approach to nonlinear system identification under missing observations with a real application Gopaluni, R Bhushan, Schön, Thomas B, and Wills, Adrian G 2009. IFAC Proceedings Volumes, 42 (10), 810–815. [Abstract] [PDF] [Presentation] [Code]

2008

  1. A particle filter approach to identification of nonlinear processes under missing observations and Gopaluni, RB 2008. The Canadian Journal of Chemical Engineering, 86 (6), 1081–1092. [Abstract] [PDF] [Presentation] [Code]
  2. An online non-intrusive method for alignment between actuators and their response centers on a paper machine Gopaluni, R Bhushan, Davies, Michael S, Loewen, Philip D, and Dumont, Guy A 2008. ISA transactions, 47 (3), 241–246. [Abstract] [PDF] [Presentation] [Code]
  3. Adaptive signal processing of asset price dynamics with predictability analysis Mamon, Rogemar S, Erlwein, Christina, and Gopaluni, R Bhushan 2008. Information Sciences, 178 (1), 203–219. [Abstract] [PDF] [Presentation] [Code]
  4. Identification of nonlinear processes with known model structure under missing observatrions and Gopaluni, Ratna Bhushan 2008. In Proceedings of the IFAC 17th World Congress, Seoul, Korea, July 6, 11 ,

2007

    2006

    1. Identification of delay dominant recycle systems Gopaluni, RB, Raghavan, H, Patwardhan, RS, Shah, SL, and Dumont, GA 2006. Journal of Process Control, 16 (9), 903–912. [Abstract] [PDF] [Presentation] [Code]
    2. Identification of Symmetric Noncausal Processes: Cross-Directional Response Modelling of Paper Machines Gopaluni, R Bhushan, Loewen, Philip D, Ammar, Mohammed, Dumont, Guy A, and Davies, Michael S 2006. In Decision and Control, 2006 45th IEEE Conference on, , 6744–6749.
    3. Identification of chemical processes with irregular output sampling Raghavan, Harigopal, Tangirala, Arun K, Bhushan Gopaluni, R, and Shah, Sirish L 2006. Control engineering practice, 14 (5), 467–480. [Abstract] [PDF] [Presentation] [Code]
    4. Autonomous alignment of CD control on paper machines Farahmand, F, Gopulani, R, Dumont, G, Davies, M, and Loewen, P 2006. In Proc. FSA Control Syst. Conf., , 203–208.

    2005

    1. Gray-box identification of dynamic models for the bleaching operation in a pulp mill Raghavan, Harigopal, Gopaluni, R Bhushan, Shah, Sirish, Pakpahan, Johan, Patwardhan, Rohit, and Robson, Chris 2005. Journal of Process Control, 15 (4), 451–468. [Abstract] [PDF] [Presentation] [Code]
    2. ROBUST ADAPTIVE CONTROL FOR STRICT-FEEDBACK NONLINEAR SYSTEMS Mizumoto, Ikuro, Gopaluni, Ratna Bhushan, Shah, Sirish L, and Iwai, Zenta 2005. Asian Journal of Control, 7 (3), 231–243. [Abstract] [PDF] [Presentation] [Code]

    2004

    1. MPC relevant identificationtuning the noise model Gopaluni, RB, Patwardhan, RS, and Shah, SL 2004. Journal of Process Control, 14 (6), 699–714. [Abstract] [PDF] [Presentation] [Code]
    2. System identification from multi-rate data Gopaluni, R Bhushan, Raghavan, Harigopal, and Shah, Sirish L 2004. IFAC Proceedings Volumes, 37 (1), 155–160. [Abstract] [PDF] [Presentation] [Code]
    3. Iterative identification and predictive control and Gopaluni, Ratna Bhushan 2004. , [Abstract] [PDF] [Presentation] [Code]

    2003

    1. The nature of data pre-filters in MPC relevant identification?open-and closed-loop issues Gopaluni, R Bhushan, Patwardhan, RS, and Shah, SL 2003. automatica, 39 (9), 1617–1626. [Abstract] [PDF] [Presentation] [Code]
    2. A robust nonlinear adaptive backstepping controller for a CSTR Gopaluni, RB, Mizumoto, Ikuro, and Shah, SL 2003. Industrial & engineering chemistry research, 42 (20), 4628–4644. [Abstract] [PDF] [Presentation] [Code]
    3. Robust Adaptive Backstepping Control Based on High-Gain Feedback and Its Application to a CSTR Control Mizumoto, Ikuro, Michino, Ryuji, Iwai, Zenta, Gopaluni, Ratna Bhushan, and Shah, Sirish L 2003. Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, 69 (10), 2667–2674. [Abstract] [PDF] [Presentation] [Code]
    4. ???????????????????????????????????? CSTR ?????? ????, , ????, , and ????, 2003. ????????? C ?, 69 (686), 2667–2674. [Abstract] [PDF] [Presentation] [Code]

    2002

    1. Experiment design for MPC relevant identification Gopaluni, Ratna Bhushan, Patwardhan, Rohit S, and Shah, Sirish L 2002. In American Control Conference, 2002. Proceedings of the 2002, 4 , 2713–2718.
    2. Bias distribution in MPC relevant identification Gopaluni, Ratna Bhushan, Patwardhan, Rohit S, and Shah, Sirish L 2002. IFAC Proceedings Volumes, 35 (1), 435–440. [Abstract] [PDF] [Presentation] [Code]
    3. Robust Adaptive Control for Strict-Feedback Nonlinear Systems with Non-Parametric Uncertainties Mizumoto, Ikuro, Gopaluni, RB, Shah, SL, and Iwai, Zenta 2002. Transactions of the Society of Instrument and Control Engineers, 38 (12), 1069–1078. [Abstract] [PDF] [Presentation] [Code]
    4. ?????????????????? Strict-Feedback ??????????????????? ????, , GOPALUNI, RB, SHAH, SL, and ????, 2002. ???????????, 38 (12), 1069–1078. [Abstract] [PDF] [Presentation] [Code]
    5. Bias distribution in MPC relevant identification 15th Triennial World Congress Gopaluni, R, Patwardhan, R, and Shah, S 2002. In , ,

    2019

    1. Design and Application of a Database-Driven PID Controller with Data-Driven Updating Algorithm Wakitani, S., Yamamoto, T., and Gopaluni, R.B. 2019. Industrial and Engineering Chemistry Research, To Appear , . [Abstract] [PDF] [DOI]
    2. Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction Wang, K., Gopaluni, R.B., Chen, J., and Song, Z. 2019. IEEE Transactions on Industrial Informatics, To Appear , . [Abstract] [PDF] [DOI]
    3. Identification of Symmetric Noncausal Processes Lu, Q., Loewen, P.D., Gopaluni, R.B., Forbes, M.G., Backstrom, J.U., Dumont, G.A., and Davies, M.S. 2019. Automatica, 103 , 515-530. [Abstract] [PDF]
    4. Systematic Development of a New Variational Autoencoder Model Based on Uncertain Data for Monitoring Nonlinear Processes Wang, K., Forbes, M.G., Gopaluni, R.B., Chen, J., and Song, Z. 2019. IEEE Access, 7 , 22554-22565. [Abstract] [PDF] [DOI]
    5. Data-Driven Dynamic Modeling and Online Monitoring for Multiphase and Multimode Batch Processes with Uneven Batch Durations Wang, K., Forbes, L, Chen, J., Song, Z., and Gopaluni, R.B. 2019. Industrial and Engineering Chemistry Research (Prof. Dominique Bonvin - Festschrift), 7 , 22554-22565. [Abstract] [PDF] [DOI]
    6. Machine Direction Adaptive Control on a Paper Machine Rippon, L. D., Lu, Q., Forbes, M.G., Gopaluni, R.B., Loewen, P.D., and Backstrom, J.U. 2019. Industrial and Engineering Chemistry Research (Prof. Sirish Shah - Festschrift), 7 , 22554-22565. [Abstract] [PDF] [DOI]
    7. Univariate model-based deadband alarm design for nonlinear processes Tulsyan, A., and Gopaluni, R.B. 2019. Industrial and Engineering Chemistry Research (Prof. Sirish Shah - Festschrift), To Appear , . [Abstract] [PDF] [DOI]
    8. Development and Characterization of a Non- Intrusive Magnetic Sensor to Measure Wear in Centrifugal Pumps Bohn, B., Khoie, R., Gopaluni, R.B., Olson, J.A., and Stoeber, B. 2019. IEEE Sensors, To Appear , . [Abstract] [PDF] [DOI]
    9. Towards Self-Driving Processes: A Deep Reinforcement Learning Approach to Control Speilberg, S., Tulsyan, A., Lawrence, N.P., Loewen, P.D., and Gopaluni, R.B. 2019. AIChE Journal, To Appear , . [Abstract] [PDF] [DOI]
    10. An economic model predictive control framework for mechanical pulping processes Tian, H., Lu, Q., Gopaluni, R.B., Zavala, V.M., and Olson, J.A. 2019. Control Engineering Practice, 85 , 100-109. [Abstract] [PDF] [DOI]

    2018

    1. A switching strategy for adaptive state estimation Tulsyan, A., Khare, S., Huang, B., Gopaluni, R.B., and Forbes, F.J. 2018. Signal Processing, 143 , 371-380. [Abstract] [PDF] [DOI]
    2. Design and Assessment of Delay Timer Alarm Systems for Nonlinear Chemical Processes Tulsyan, A., Alrowaie, F., and Gopaluni, R.B. 2018. AIChE Journal, 64((1) , 77-90. [Abstract] [PDF] [DOI]
    3. Application of neural networks for optimal-setpoint design and MPC control in biological wastewater treatment Sadeghassadi, M., Macnab, C.J.B., Gopaluni, R.B., and Westwick, D. 2018. Computers & Chemical Engineering, 115 , 150–160. [Abstract] [PDF] [DOI]
    4. Locality Preserving Discriminative Canonical Variate Analysis for Fault Diagnosis Lu, Q., Jiang, B., Gopaluni, R.B., Loewen, P.D., and Braatz, R.D. 2018. Computers & Chemical Engineering, 117 , 309-319. [Abstract] [PDF] [DOI]
    5. Sparse canonical variate analysis approach for process monitoring Lu, Q., Jiang, B., Gopaluni, R.B., Loewen, P.D., and Braatz, R.D. 2018. Journal of Process Control, 71 , 90-102. [Abstract] [PDF] [DOI]

    2017

    1. Performance Assessment of Cross-Directional Control for Paper Machines Lu, Q., Forbes, M.G., Gopaluni, R.B., Loewen, P.D., Backström, J.U., and Dumont, G.A. 2017. IEEE Transactions on Control Systems Technology, 25 (1), 208–221. [Abstract] [PDF] [DOI]
    2. A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty Zamar, D.S., Gopaluni, R.B., Sokhansanj, S., and Newlands, N.K. 2017. Computers & Chemical Engineering, 97 , 114–123. [Abstract] [PDF] [DOI]
    3. Optimization of sawmill residues collection for bioenergy production Zamar, D.S., Gopaluni, R.B., and Sokhansanj, S. 2017. Applied Energy, 202 , 487–495. [Abstract] [PDF] [DOI]

    2016

    1. A comprehensive compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects Vahidi, O., Kwok, K.E., Gopaluni, R.B., and Knop, F.K. 2016. Medical & biological engineering & computing, 54 (9), 1383–1398. [Abstract] [PDF] [DOI]
    2. Simple Self-Administered Method for Assessing Insulin Sensitivity in Diabetic Patients Barazandegan, M., Ekram, F., Kwok, E., and Gopaluni, R.B. 2016. Journal of Medical and Biological Engineering, 36 (2), 197–205. [Abstract] [PDF] [DOI]
    3. LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control Torchio, M., Magni, L., Gopaluni, R.B., Braatz, R.D., and Raimondo, D.M. 2016. Journal of The Electrochemical Society, 163 (7), A1192–A1205. [Abstract] [PDF] [DOI] [Code]
    4. Regularized maximum likelihood estimation of sparse stochastic monomolecular biochemical reaction networks Jang, Hong, Kim, Kwang-Ki K, Braatz, Richard D, Gopaluni, R Bhushan, and Lee, Jay H 2016. Computers & Chemical Engineering, 90 , 111–120. [Abstract] [PDF] [Presentation] [Code]
    5. Economic Optimization of Sawmill Residues Collection for Bioenergy Conversion Zamar, David S, Gopaluni, Bhushan, Sokhansanj, Shahab, and Ebadian, Mahmood 2016. IFAC-PapersOnLine, 49 (7), 857–862. [Abstract] [PDF] [Presentation] [Code]
    6. State-of-charge estimation in lithium-ion batteries: A particle filter approach Tulsyan, Aditya, Tsai, Yiting, Gopaluni, R Bhushan, and Braatz, Richard D 2016. Journal of Power Sources, 331 , 208–223. [Abstract] [PDF] [Presentation] [Code]
    7. Particle filtering without tears: A primer for beginners Tulsyan, Aditya, Gopaluni, R Bhushan, and Khare, Swanand R 2016. Computers & Chemical Engineering, 95 , 130–145. [Abstract] [PDF] [Presentation] [Code]

    2015

    1. Moving-Horizon Predictive Input Design for Closed-Loop Identification Yousefi, M, Rippon, LD, Forbes, MG, Gopaluni, RB, Loewen, PD, Dumont, GA, and Backstrom, J 2015. IFAC-PapersOnLine, 48 (8), 135–140. [Abstract] [PDF] [Presentation] [Code]
    2. Detection of abnormalities in type II diabetic patients using particle filters Vahidi, Omid, Gopaluni, R Bhushan, and Kwok, Ezra 2015. Journal of Medical and Biological Engineering, 35 (2), 188–201. [Abstract] [PDF] [Presentation] [Code]
    3. Impact of model plant mismatch on performance of control systems: An application to paper machine control Yousefi, M, Gopaluni, RB, Loewen, PD, Forbes, MG, Dumont, GA, and Backstrom, J 2015. Control Engineering Practice, 43 , 59–68. [Abstract] [PDF] [Presentation] [Code]
    4. A Novel Algorithm for Model-Plant Mismatch Detection for Model Predictive Controllers Tsai, Yiting, Gopaluni, RB, Marshman, D, and Chmelyk, T 2015. IFAC-PapersOnLine, 48 (8), 746–752. [Abstract] [PDF] [Presentation] [Code]
    5. Overload Detection in Semi-Autogenous Grinding: A Nonlinear Process Monitoring Approach McClure, KS, and Gopaluni, RB 2015. IFAC-PapersOnLine, 48 (8), 960–965. [Abstract] [PDF] [Presentation] [Code]
    6. Model predictive control in industry: Challenges and opportunities Forbes, Michael G, Patwardhan, Rohit S, Hamadah, Hamza, and Gopaluni, R Bhushan 2015. IFAC-PapersOnLine, 48 (8), 531–538. [Abstract] [PDF] [Presentation] [Code]
    7. Robust Optimization of Competing Biomass Supply Chains Under Feedstock Uncertainty Zamar, David S, Gopaluni, Bhushan, Sokhansanj, Shahab, and Newlands, Nathaniel K 2015. IFAC-PapersOnLine, 48 (8), 1222–1227. [Abstract] [PDF] [Presentation] [Code]
    8. Assessment of type II diabetes mellitus using irregularly sampled measurements with missing data Barazandegan, Melissa, Ekram, Fatemeh, Kwok, Ezra, Gopaluni, Bhushan, and Tulsyan, Aditya 2015. Bioprocess and biosystems engineering, 38 (4), 615–629. [Abstract] [PDF] [Presentation] [Code]

    2014

    1. Robust level control of a dry-surge ore pile McClure, Kenneth Scott, Nagamune, Ryozo, Marshman, Devin, Chmelyk, Terrance, and Gopaluni, Bhushan 2014. The Canadian Journal of Chemical Engineering, 92 (3), 486–495.
    2. Performance assessment, diagnosis, and optimal selection of non-linear state filters Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2014. Journal of Process Control, 24 (2), 460–478. [Abstract] [PDF] [Presentation] [Code]
    3. Fault Isolation based on General Observer Scheme in Stochastic Non-linear State-Space Models Using Particle Filters Alrowaie, F, Kwok, KE, and Gopaluni, RB 2014. ADCONP, ,
    4. A moving horizon approach to input design for closed loop identification Patwardhan, Rohit S, and Goapluni, R Bhushan 2014. Journal of Process Control, 24 (3), 188–202. [Abstract] [PDF] [Presentation] [Code]
    5. Increased CHO cell fed-batch monoclonal antibody production using the autophagy inhibitor 3-MA or gradually increasing osmolality Nasseri, S Soroush, Ghaffari, Navid, Braasch, Katrin, Jardon, Mario A, Butler, Michael, Kennard, Malcolm, Gopaluni, Bhushan, and Piret, James M 2014. Biochemical Engineering Journal, 91 , 37–45. [Abstract] [PDF] [Presentation] [Code]
    6. SELF-ASSESSMENT OF INSULIN SENSITIVITY Barazandegan, M, Ekram, F, Kwok, KE, and Gopaluni, RB 2014. SELF, ,

    2013

    1. A moving horizon approach to multivariable input design in general linear systems with constraints Patwardhan, RS, and Gopaluni, RB 2013. IFAC Proceedings Volumes, 46 (32), 577–582. [Abstract] [PDF] [Presentation] [Code]
    2. Use of Molecular Dynamics for the Refinement of an Electrostatic Model for the In Silico Design of a Polymer Antidote for the Anticoagulant Fondaparinux Cajiao, Adriana, Kwok, Ezra, Gopaluni, Bhushan, and Kizhakkedathu, Jayachandran N 2013. Journal of medical engineering, 2013 , [Abstract] [PDF] [Presentation] [Code]
    3. A particle filter approach to approximate posterior Cramér-Rao lower bound: The case of hidden states Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. IEEE Transactions on Aerospace and Electronic Systems, 49 (4), 2478–2495. [Abstract] [PDF] [Presentation] [Code]
    4. On-line Bayesian parameter estimation in general non-linear state-space models: a tutorial and new results Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. arXiv preprint arXiv:1307.3490, ,
    5. Input design for Bayesian identification of non-linear state-space models Tulsyan, Aditya, Khare, Swanand R, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. arXiv preprint arXiv:1307.6258, ,
    6. Error analysis in Bayesian identification of non-linear state-space models Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. arXiv preprint arXiv:1307.6254, ,
    7. Nonlinear process monitoring using supervised locally linear embedding projection McClure, Kenneth S, Gopaluni, R Bhushan, Chmelyk, Terrance, Marshman, Devin, and Shah, Sirish L 2013. Industrial & Engineering Chemistry Research, 53 (13), 5205–5216. [Abstract] [PDF] [Presentation] [Code]
    8. Bayesian identification of non-linear state-space models: Part II-Error Analysis Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. IFAC Proceedings Volumes, 46 (32), 631–636. [Abstract] [PDF] [Presentation] [Code]
    9. Bayesian identification of non-linear state-space models: Part I-Input design Tulsyan, Aditya, Khare, Swanand R, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. IFAC Proceedings Volumes, 46 (32), 774–779. [Abstract] [PDF] [Presentation] [Code]
    10. Evaluation of adaptive extended Kalman filter algorithms for state estimation in presence of model-plant mismatch Bavdekar, Vinay A, Gopaluni, R Bhushan, and Shah, Sirish L 2013. IFAC Proceedings Volumes, 46 (32), 184–189. [Abstract] [PDF] [Presentation] [Code]
    11. State of charge estimation in Li-ion batteries using an isothermal pseudo two-dimensional model Gopaluni, R Bhushan, and Braatz, Richard D 2013. IFAC Proceedings Volumes, 46 (32), 135–140. [Abstract] [PDF] [Presentation] [Code]
    12. A Comparison of Moving Horizon and Bayesian State Estimators with an Application to a pH Process Bavdekar, Vinay A, Gopaluni, R Bhushan, and Shah, Sirish L 2013. IFAC Proceedings Volumes, 46 (32), 160–165. [Abstract] [PDF] [Presentation] [Code]
    13. On simultaneous on-line state and parameter estimation in non-linear state-space models Tulsyan, Aditya, Huang, Biao, Gopaluni, R Bhushan, and Forbes, J Fraser 2013. Journal of Process Control, 23 (4), 516–526. [Abstract] [PDF] [Presentation] [Code]

    2012

    1. A feedback glucose control strategy for type II diabetes mellitus based on fuzzy logic Ekram, F, Sun, L, Vahidi, O, Kwok, E, and Gopaluni, RB 2012. The Canadian Journal of Chemical Engineering, 90 (6), 1411–1417. [Abstract] [PDF] [Presentation] [Code]
    2. Fault detection and isolation in stochastic non-linear state-space models using particle filters Alrowaie, F, Gopaluni, RB, and Kwok, KE 2012. Control Engineering Practice, 20 (10), 1016–1032. [Abstract] [PDF] [Presentation] [Code]
    3. Performance assessment of nonlinear state filters Tulsyan, Aditya, Huang, Biao, Gopaluni, RB, and Forbes, J Fraser 2012. IFAC Proceedings Volumes, 45 (15), 371–376. [Abstract] [PDF] [Presentation] [Code]
    4. Nonlinear Bayesian state estimation: A review of recent developments Patwardhan, Sachin C, Narasimhan, Shankar, Jagadeesan, Prakash, Gopaluni, Bhushan, and L Shah, Sirish 2012. Control Engineering Practice, 20 (10), 933–953. [Abstract] [PDF] [Presentation] [Code]
    5. Editorial: 4th Symposium on Advanced Control of Industrial Processes (ADCONIP) Gudi, Ravi, Gopaluni, Bhushan, and Huang, Biao 2012. Control Engineering Practice, 20 (10), 931–932. [Abstract] [PDF] [Presentation] [Code]
    6. Parameter estimation in models with hidden variables: An application to a biotech process Jang, Seunghee S, Hoz, Hector, Ben-zvi, Amos, McCaffrey, William C, and Gopaluni, R Bhushan 2012. The Canadian Journal of Chemical Engineering, 90 (3), 690–702. [Abstract] [PDF] [Presentation] [Code]

    2011

    1. Developing a physiological model for type II diabetes mellitus Vahidi, O, Kwok, KE, Gopaluni, RB, and Sun, L 2011. Biochemical Engineering Journal, 55 (1), 7–16. [Abstract] [PDF] [Presentation] [Code]
    2. Characterization of gas–solid fluidization: A comparative study of acoustic and pressure signals Li, Yan-qin, Grace, John R, Gopaluni, R Bhushan, Bi, Hsiaotao, Lim, C Jim, and Ellis, Naoko 2011. Powder technology, 214 (2), 200–210. [Abstract] [PDF] [Presentation] [Code]
    3. Parameter estimation in nonlinear chemical and biological processes with unmeasured variables from small data sets Jang, SS, and Gopaluni, RB 2011. Chemical Engineering Science, 66 (12), 2774–2787. [Abstract] [PDF] [Presentation] [Code]
    4. Pharmacokinetic-Pharmacodynamic Modeling of Metformin for the Treatment of Type II Diabetes Mellitus Sun, Lin, Kwok, Ezra, Gopaluni, Bhushan, and Vahidi, Omid 2011. The Open Biomedical Engineering Journal, 5 , 1. [Abstract] [PDF] [Presentation] [Code]
    5. In Silico Design of Polymeric Antidote for Anticoagulant Fondaparinux Cajiao, Adriana, Gopaluni, Bhushan, Kwok, Ezra, and Kizhakkedathu, Jayachandran N 2011. Journal of Medical and Biological Engineering, 31 (2), 129–134. [Abstract] [PDF] [Presentation] [Code]
    6. Reconstructing Paper Machine Sheet Process Data Variation Using Compressive Sensing Davies, Michael, Gopaluni, Bhushan, Loewen, Philip, Towfighi, Parisa, and Dumont, Guy 2011. IFAC Proceedings Volumes, 44 (1), 4266–4271. [Abstract] [PDF] [Presentation] [Code]

    2010

    1. A comparison of simultaneous state and parameter estimation schemes for a continuous fermentor reactor Chitralekha, Saneej B, Prakash, J, Raghavan, H, Gopaluni, RB, and Shah, Sirish L 2010. Journal of Process Control, 20 (8), 934–943. [Abstract] [PDF] [Presentation] [Code]
    2. Nonlinear system identification under missing observations: The case of unknown model structure and Gopaluni, R Bhushan 2010. Journal of Process Control, 20 (3), 314–324. [Abstract] [PDF] [Presentation] [Code]
    3. Energy optimization in a pulp and paper mill cogeneration facility Marshman, DJ, Chmelyk, T, Sidhu, MS, Gopaluni, RB, and Dumont, GA 2010. Applied Energy, 87 (11), 3514–3525. [Abstract] [PDF] [Presentation] [Code]
    4. Economic performance assessment with optimized LQG benchmarking in MIMO systems Marshman, Devin James, Chmelyk, Terrance, Sidhu, MS, Gopaluni, Ratna Bhushan, and Dumont, GA 2010. IFAC Proceedings Volumes, 43 (5), 769–774. [Abstract] [PDF] [Presentation] [Code]
    5. Special series of articles on process control Gopaluni, RB, and Duchesne, C 2010. The Canadian Journal of Chemical Engineering, 88 (5), 695–695. [Abstract] [PDF] [Presentation] [Code]
    6. Nonlinear System Identification from Small Data Sets Gopaluni, R Bhushan, and Marshman, Devin 2010. IFAC Proceedings Volumes, 43 (5), 589–594. [Abstract] [PDF] [Presentation] [Code]

    2009

    1. Identification of nonlinear state-space models: the case of unknown model structure and Gopaluni, R Bhushan 2009. IFAC Proceedings Volumes, 42 (11), 470–475. [Abstract] [PDF] [Presentation] [Code]
    2. A note on separating machine direction and cross machine data on a paper machine Gopaluni, RB, Davies, MS, Loewen, PD, Stewart, GE, and Dumont, GA 2009. NORDIC Pulp & Paper Research Journal, 24 (3), 273–277.
    3. Particle filter approach to nonlinear system identification under missing observations with a real application Gopaluni, R Bhushan, Schön, Thomas B, and Wills, Adrian G 2009. IFAC Proceedings Volumes, 42 (10), 810–815. [Abstract] [PDF] [Presentation] [Code]

    2008

    1. A particle filter approach to identification of nonlinear processes under missing observations and Gopaluni, RB 2008. The Canadian Journal of Chemical Engineering, 86 (6), 1081–1092. [Abstract] [PDF] [Presentation] [Code]
    2. An online non-intrusive method for alignment between actuators and their response centers on a paper machine Gopaluni, R Bhushan, Davies, Michael S, Loewen, Philip D, and Dumont, Guy A 2008. ISA transactions, 47 (3), 241–246. [Abstract] [PDF] [Presentation] [Code]
    3. Adaptive signal processing of asset price dynamics with predictability analysis Mamon, Rogemar S, Erlwein, Christina, and Gopaluni, R Bhushan 2008. Information Sciences, 178 (1), 203–219. [Abstract] [PDF] [Presentation] [Code]

    2007

      2006

      1. Identification of delay dominant recycle systems Gopaluni, RB, Raghavan, H, Patwardhan, RS, Shah, SL, and Dumont, GA 2006. Journal of Process Control, 16 (9), 903–912. [Abstract] [PDF] [Presentation] [Code]
      2. Identification of chemical processes with irregular output sampling Raghavan, Harigopal, Tangirala, Arun K, Bhushan Gopaluni, R, and Shah, Sirish L 2006. Control engineering practice, 14 (5), 467–480. [Abstract] [PDF] [Presentation] [Code]

      2005

      1. Gray-box identification of dynamic models for the bleaching operation in a pulp mill Raghavan, Harigopal, Gopaluni, R Bhushan, Shah, Sirish, Pakpahan, Johan, Patwardhan, Rohit, and Robson, Chris 2005. Journal of Process Control, 15 (4), 451–468. [Abstract] [PDF] [Presentation] [Code]
      2. ROBUST ADAPTIVE CONTROL FOR STRICT-FEEDBACK NONLINEAR SYSTEMS Mizumoto, Ikuro, Gopaluni, Ratna Bhushan, Shah, Sirish L, and Iwai, Zenta 2005. Asian Journal of Control, 7 (3), 231–243. [Abstract] [PDF] [Presentation] [Code]

      2004

      1. MPC relevant identificationtuning the noise model Gopaluni, RB, Patwardhan, RS, and Shah, SL 2004. Journal of Process Control, 14 (6), 699–714. [Abstract] [PDF] [Presentation] [Code]
      2. System identification from multi-rate data Gopaluni, R Bhushan, Raghavan, Harigopal, and Shah, Sirish L 2004. IFAC Proceedings Volumes, 37 (1), 155–160. [Abstract] [PDF] [Presentation] [Code]

      2003

      1. The nature of data pre-filters in MPC relevant identification?open-and closed-loop issues Gopaluni, R Bhushan, Patwardhan, RS, and Shah, SL 2003. automatica, 39 (9), 1617–1626. [Abstract] [PDF] [Presentation] [Code]
      2. A robust nonlinear adaptive backstepping controller for a CSTR Gopaluni, RB, Mizumoto, Ikuro, and Shah, SL 2003. Industrial & engineering chemistry research, 42 (20), 4628–4644. [Abstract] [PDF] [Presentation] [Code]
      3. Robust Adaptive Backstepping Control Based on High-Gain Feedback and Its Application to a CSTR Control Mizumoto, Ikuro, Michino, Ryuji, Iwai, Zenta, Gopaluni, Ratna Bhushan, and Shah, Sirish L 2003. Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, 69 (10), 2667–2674. [Abstract] [PDF] [Presentation] [Code]
      4. ???????????????????????????????????? CSTR ?????? ????, , ????, , and ????, 2003. ????????? C ?, 69 (686), 2667–2674. [Abstract] [PDF] [Presentation] [Code]

      2002

      1. Bias distribution in MPC relevant identification Gopaluni, Ratna Bhushan, Patwardhan, Rohit S, and Shah, Sirish L 2002. IFAC Proceedings Volumes, 35 (1), 435–440. [Abstract] [PDF] [Presentation] [Code]
      2. Robust Adaptive Control for Strict-Feedback Nonlinear Systems with Non-Parametric Uncertainties Mizumoto, Ikuro, Gopaluni, RB, Shah, SL, and Iwai, Zenta 2002. Transactions of the Society of Instrument and Control Engineers, 38 (12), 1069–1078. [Abstract] [PDF] [Presentation] [Code]
      3. ?????????????????? Strict-Feedback ??????????????????? ????, , GOPALUNI, RB, SHAH, SL, and ????, 2002. ???????????, 38 (12), 1069–1078. [Abstract] [PDF] [Presentation] [Code]

      2019

      1. Assessment of Simplifications to a Pseudo–2D Electrochemical Model of Li-ion Batteries Kong, X.R., Wetton, B., and Gopaluni, R.B. 2019. In Proceedings of DYCOPS Conference, , 946-951. [Abstract] [PDF]

      2018

      1. Pattern and Knowledge Extraction using Process Data Analytics: A Tutorial Tsai, Y., Lu, Q., Rippon, L., Lim, S., Tulsyan, A., and Gopaluni, R.B. 2018. In Proceedings of ADCHEM Conference, 51 , 13-18. [Abstract] [PDF] [DOI]
      2. A Deep Learning Architecture for Predictive Control Spielberg, S., Tulsyan, A., Gopaluni, R.B., and Loewen, P.D. 2018. In Proceedings of ADCHEM Conference, Shenyang, China, 51 , 512-517. [Abstract] [PDF] [DOI]
      3. An Efficient Model Based Control Algorithm for the Determination of an Optimal Control Policy for a Constrained Stochastic Linear System Prakash, J., Zamar, D., Gopaluni, R.B., and Kwok, E. 2018. In Proceedings of ADCHEM Conference, 51 , 584-589. [Abstract] [PDF] [DOI]
      4. State of Health Estimation for Lithium-Ion Batteries Kong, X., Bonakdarpour, A., Wetton, B.T., Wilkinson, D.P., and Gopaluni, R.B. 2018. In Proceedings of ADCHEM Conference, 51 , 661-665. [Abstract] [PDF] [DOI]

      2017

      1. A Constrained k-means and Nearest Neighbor Approach for Route Optimization: With an application to the Bale Collection Zamar, D., Gopaluni, R.B., and Sokhansanj, S. 2017. In Proceedings of IFAC World Congress, , 12125-12130. [Abstract] [PDF] [Presentation]
      2. Model-Plant Mismatch Detection with Support Vector Machines Lu, Q., Gopaluni, R.B., Forbes, M.G., Loewen, P.D., Backstrom, J.U., and Dumont, G.A. 2017. In Proceedings of IFAC World Congress, , 7993-7998. [Abstract] [PDF]
      3. Noncausal Modeling and Closed-Loop Optimal Input Design for Cross-Directional Processes of Paper Machines Lu, Q., Gopaluni, R.B., Forbes, M.G., Loewen, P.D., Backstrom, J.U., and Dumont, G.A. 2017. In Proceedings of American Control Conference, , 2837-2842. [Abstract] [PDF] [Presentation]
      4. Deep Reinforcement Learning Approaches for Process Control Spielberg, S.P., Gopaluni, R.B., and Loewen, P.D. 2017. In Proceedings of ADCONIP, , 201-206. [Abstract] [PDF]

      2016

      1. Model-based detection of organ dysfunction and faults in insulin infusion devices for type 2 diabetic patients Barazandegan, M, Kwok, KE, and Gopaluni, RB 2016. In American Control Conference (ACC), 2016, , 3994–3999.
      2. Economic nonlinear model predictive control for mechanical pulping processes Tian, Hui, Lu, Qiugang, Gopaluni, R Bhushan, Zavala, Victor M, and Olson, James A 2016. In American Control Conference (ACC), 2016, , 1796–1801.
      3. Robust model-based delay timer alarm for non-linear processes Tulsyan, Aditya, and Gopaluni, R Bhushan 2016. In American Control Conference (ACC), 2016, , 2989–2994.
      4. Multiobjective economic model predictive control of mechanical pulping processes Tian, Hui, Lu, Qiugang, Gopaluni, R Bhushan, and Zavala, Victor M 2016. In Decision and Control (CDC), 2016 IEEE 55th Conference on, , 4040–4045.

      2015

      1. Detecting model-plant mismatch without external excitation Yousefi, Mahdi, Lu, Qiugang, Gopaluni, R Bhushan, Loewen, Philip D, Forbes, Michael G, Dumont, Guy Albert, and Backstrom, J 2015. In American Control Conference (ACC), 2015, , 4976–4981.
      2. Cross-directional controller performance monitoring for paper machines Lu, Qiugang, Rippon, Lee D, Gopaluni, R Bhushan, Forbes, Michael G, Loewen, Philip D, Backstrom, Johan, and Dumont, Guy A 2015. In American Control Conference (ACC), 2015, , 4970–4975.
      3. Real-time model predictive control for the optimal charging of a lithium-ion battery Torchio, Marcello, Wolff, Nicolas A, Raimondo, Davide M, Magni, Lalo, Krewer, Ulrike, Gopaluni, R Bushan, Paulson, Joel A, and Braatz, Richard D 2015. In American Control Conference (ACC), 2015, , 4536–4541.
      4. Evaluation of treatment regimens for blood glucose regulation in type II diabetes using pharmacokinetic-pharmacodynamic modeling Ekram, Fatemeh, Barazandegan, Melissa, Kwok, Ezra, and Gopaluni, Bhushan 2015. In Control Conference (CCC), 2015 34th Chinese, , 8519–8524.
      5. A magnetic sensor to measure wear in centrifugal pumps Khoie, Ramin, Gopaluni, Bhushan, Olson, James A, and Stoeber, Boris 2015. In SENSORS, 2015 IEEE, , 1–4.

      2014

      1. Sparse identification in chemical master equations for monomolecular reaction networks Kim, Kwang-Ki K, Jang, Hong, Gopaluni, R Bhushan, Lee, Jay H, and Braatz, Richard D 2014. In American Control Conference (ACC), 2014, , 3698–3703.
      2. Sensitivity of controller performance indices to model-plant mismatch: An application to paper machine control Yousefi, Mahdi, Forbes, Michael G, Gopaluni, R Bhushan, Dumont, Guy Albert, Backstrom, J, and Malhotra, A 2014. In American Control Conference (ACC), 2014, , 3506–3511.
      3. Sensitivity of mimo controller performance to model-plant mismatch, with applications to paper machine control Yousefi, Mahdi, Forbes, Michael G, Gopaluni, R Bhushan, Loewen, Philip D, Dumont, Guy Albert, and Backstrom, J 2014. In Control Applications (CCA), 2014 IEEE Conference on, , 204–209.
      4. Alarm design for nonlinear stochastic systems Alrowaie, F, Gopaluni, RB, and Kwok, KE 2014. In Intelligent Control and Automation (WCICA), 2014 11th World Congress on, , 473–479.

      2013

      1. Constrained dual ensemble Kalman filter for state and parameter estimation Bavdekar, Vinay A, Prakash, Jagdeesan, Shah, Sirish L, and Gopaluni, R Bhushan 2013. In American Control Conference (ACC), 2013, , 3093–3098.
      2. Optimal control and state estimation of lithium-ion batteries using reformulated models Suthar, Bharatkumar, Ramadesigan, Venkatasailanathan, Northrop, Paul WC, Gopaluni, Bhushan, Santhanagopalan, Shriram, Braatz, Richard D, and Subramanian, Venkat R 2013. In American Control Conference (ACC), 2013, , 5350–5355.

      2012

        2011

        1. Detection of organ dysfunction in type II diabetic patients Vahidi, O, Gopaluni, RB, and Kwok, KE 2011. In American Control Conference (ACC), 2011, , 4769–4774.
        2. An algorithm for fault detection in stochastic non-linear state-space models using particle filters Alrowaie, F, Kwok, KE, and Gopaluni, RB 2011. In Advanced Control of Industrial Processes (ADCONIP), 2011 International Symposium on, , 60–65.
        3. Nonlinear bayesian state estimation: Review and recent trends Prakash, J, Gopaluni, RB, Patwardhan, Sachin C, Narasimhan, Shankar, and Shah, Sirish L 2011. In Advanced Control of Industrial Processes (ADCONIP), 2011 International Symposium on, , 450–455.
        4. Input Design for Nonlinear Stochastic Dynamic Systems-A Particle Filter Approach Gopaluni, R Bhushan, Schön, Thomas B, and Wills, Adrian G 2011. In IFAC World Congress, 18 (1), 13191–13196.
        5. Reconstructing Variation in a Sheet of Paper Using Compressive Sensing Towfighi, Parisa, Dumont, Guy, Davies, Michael S, Gopaluni, Bhushan, and Loewen, Philip D 2011. In Proceedings of IFAC World Congress, 18 (1), 4266–4271.
        6. A Feedback Glucose Control Strategy for Type II Diabetes Mellitus Sun, Lin, Kwok, Ezra, Gopaluni, Bhushan, and Vahidi, Omid 2011. In Advanced Control of Industrial Processes (ADCONIP), 2011 International Symposium on, , 349–352.

        2010

        1. Development of a physiological model forpatients with type 2 diabetes mellitus Vahidi, O, Kwok, KE, Gopaluni, RB, and Sun, L 2010. In American Control Conference (ACC), 2010, , 2027–2032.

        2009

        1. Comparison of expectation-maximization based parameter estimation using particle filter, unscented and extended Kalman filtering techniques Chitralekha, Saneej, Prakash, Jagadeesan, Raghavan, Harigopal, Gopaluni, Ratna Bhushan, and Shah, Sirish 2009. In IFAC Conference on System Identification, 15 (1), 804–809.

        2008

        1. Identification of nonlinear processes with known model structure under missing observatrions and Gopaluni, Ratna Bhushan 2008. In Proceedings of the IFAC 17th World Congress, Seoul, Korea, July 6, 11 ,

        2007

          2006

          1. Identification of Symmetric Noncausal Processes: Cross-Directional Response Modelling of Paper Machines Gopaluni, R Bhushan, Loewen, Philip D, Ammar, Mohammed, Dumont, Guy A, and Davies, Michael S 2006. In Decision and Control, 2006 45th IEEE Conference on, , 6744–6749.
          2. Autonomous alignment of CD control on paper machines Farahmand, F, Gopulani, R, Dumont, G, Davies, M, and Loewen, P 2006. In Proc. FSA Control Syst. Conf., , 203–208.

          2005

            2004

              2003

                2002

                1. Experiment design for MPC relevant identification Gopaluni, Ratna Bhushan, Patwardhan, Rohit S, and Shah, Sirish L 2002. In American Control Conference, 2002. Proceedings of the 2002, 4 , 2713–2718.
                2. Bias distribution in MPC relevant identification 15th Triennial World Congress Gopaluni, R, Patwardhan, R, and Shah, S 2002. In , ,