Shah, Sirish L. - University of Alberta - Department of Chemical and Materials Engineering

个人简介

Dr. Shah's research interests lie in the broad area of advanced process control algorithms and methods for monitoring process and controller performance. Specifically, the focus of Dr. Shah's more recent research activity has been in the area of multivariate statistical analysis of plant data for control loop performance assessment, process monitoring, fault diagnosis, and development of new control-relevant identification algorithms for use in the design of model-based predictive controllers.He is a past winner of the D.G. Fisher award of the CSChE for significant contributions in the Systems and Control area, as well as the NSERC University-Industry Synergy Award.

研究领域

computer process control; system identification; adaptive control; multimedia; real-time systems

近期论文

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Duan, P., F. Yang, T.Chen and S.L. Shah, “Direct Causality Detection via the Transfer Entropy Approach”, Article in press with the IEEE TCST, 2013 Kiasi, F., J. Prakash and S.L. Shah, , “An Alternative Approach to Implementation of the Generalized Likelihood Ratio Test for Fault Detection and Isolation”, Article in press with IEC Research, July 2013. Kiasi, F., J. Prakash, S. Patwardhan and S.L. Shah, “A Unified Framework for Fault Detection & Isolation of Sensor & Actuator Biases in Linear Time Invariant Systems using Marginalized Likelihood Ratio Test with Uniform Priors”, Accepted for publication in the J. of Process Control, August 2013. Gunda, N.S.K., M. Singh, Y. Purwar, S. L. Shah, K. Kaur, S.K. Mitra, “Micro-spot with integrated pillars (MSIP) for detection of dengue virus NS1”, Biomed Microdevices, Springer, 5 July 2013. Shenoy, A.V., J. Prakash, V. Prasad, S.L. Shah and K.B. McAuley, “Practical issues in state estimation using particle filters: Case studies with polymer reactors”, Accepted for publication in the Journal of Process Control, 2012 Patwardhan, S., S. Narasimhan, J. Prakash, R.B. Gopaluni and S.L. Shah, “ Nonlinear Bayesian state estimation: A review of recent developments”, Control Engineering Practice, Vol. 20, 10, pp 933-953, 2012. Yang, F., S. L. Shah and D. Xiao, “Improved correlation analysis and visualization of industrial alarm data”, ISA Transactions, 51(4), pp 499-506, 2012. Jiang, H., S.L. SHAH, B. Huang, B. Wilson, R. Patwardhan and F. Szeto, “ Model and performance analysis of two industrial MPCs”, Control Engineering Practice, (20), 2012, pp 219-235. Shardt, Y. A.W., Y. Zhao, F. Qi, K.H. Lee, X. Yu, B. Huang and S.L. Shah, “Determining the state of a Process Control System: Current trends and future challenges”, Canadian Journal of Chemical Engineering, 90 (2), pp. 217–245, 2012. Nadadoor, V.R., H. De la Hoz Siegler, S. L. SHAH, W. C. McCaffrey, and A. Benzvi, "Online Sensor for Monitoring a Microalgal Bioreactor System Using Support Vector Regression", Chemometrics and Intelligent Laboratory Systems, Vol 110, Issue 1, 2012. Yang, F., S. L. Shah and D. Xiao, “Signed directed graph modeling and validation of industrial processes by process knowledge and process data”, International Journal of Applied Mathematics and Computer Science, 22 (1), pp 41-53, 2012. Purwar, Y., S.L. Shah, G. Clarke, A. Almugairi, and A. Muehlenbachs, “ Automated and unsupervised detection of malarial parasite in microscopic images”, Malaria Journal, 10, 364, December 2011. Narang, A., SHAH, S. L., Chen, T., “Continuous-time model identification of fractional order models with time delays”, IET Control Theory Appl., Vol. 5 (7), pp. 900–912, 2011. Nadadoo, V.R., A. Benzvi, and S. L. SHAH, "Inferring Gene Networks Using Robust Statistical Techniques", Statistical Applications in Genetics and Molecular Biology: Vol. 10, 1, 2011. (Available for download in May 2011; for the first 3 months thereafter this was one of the most highly ranked paper in terms of number of downloads). Prakash, J.,, S.C. Patwardhan, and S.L.SHAH, “On the Choice of Importance Distributions for Unconstrained and Constrained State Estimation Using Particle Filter, J. Process Control, 21, pp. 3-16, 2011. Iqbal, M.H., U. SUNDARARAJ, S. L. Shah, “Identification of Transient Response of a Plasticating Twin Screw Extruder due to the Excitation in the Feed Rate”, Polymer Engineering and Science, Vol. 51, No, 3, 482-491, 2011. Jampana, P.V. and S.L.SHAH “A Novel Method for Interface Level Detection in a Separation Cell”, Machine Vision and Applications (Springer Journal), Published On-line 17 July 2011, 16 Pages. Yang, F., D. Xiao, and S.L. SHAH, Qualitative fault detection and hazard analysis based on signed directed graphs for large-scale complex systems, in Fault Detection, IN-TECH, March 2010: 15-50 (ISBN: 978-953-307-037-7) Prakash, J., S.C. Patwardhan and S. L. SHAH, “Constrained State Estimation using Ensemble Kalman Filter”, Ind. Eng. Chem. Res. 2010, 49 (5), pp. 2242–2253. Prakash, J., S.C. Patwardhan, and S.L.SHAH, “State Estimation and Nonlinear Predictive Control of Autonomous Hybrid System Using Derivative Free State Estimators”, J. Process Control, 20 (7), pp. 787-799, 2010. Chitralekha, S.B. and S.L. SHAH, “Application of Support Vector Regression for Developing SoftSensors for Nonlinear Processes”, Canadian Journal of Chemical Engineering, Volume 88, Issue 5, Pages 696 – 709, October 2010. Chitralekha, S.B., J. Prakash, H. Raghavan, R. B. Gopaluni and S. L. SHAH, “A Comparison of Simultaneous State and Parameter Estimation Schemes for a Continuous Fermentor Reactor”, Journal of Process Control, Volume 20, Issue 8, Pages 934 – 943, September 2010. Danesh Pour,N., B. HUANG, S.L. Shah ,” Performance assessment of advanced supervisory–regulatory control systems with subspace LQG benchmark” , Automatica, Volume 46, Issue 8, August 2010, Pages 1363-1368 Danesh Pour,N., B. HUANG, S.L. Shah ,” Subspace approach to identification of step response model from closed-loop data”, Industrial & Engineering Chemistry Research, 2010, 49 (18), pp 8558-8567 Badwe,A.S., R.S. Patwardhan, S.L. SHAH, S.C. Patwardhan and R.D. Gudi, (2010) Quantifying the impact of model-plant mismatch on controller performance, Journal of Process Control, 20(4), 408-425