Department of Chemical Engineering
IIT Madras

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  1. Narasimhan, S., R.S.H. Mah, A.C. Tamhane, J.W. Woodward, and J.C.Hale, “A Composite Statistical  Test  for  Detecting  Changes  of Steady States,”   AIChE J.,  32, 1409-1418 (1986).

  2. Narasimhan, S., C.S. Kao, and R.S.H. Mah, “Detecting  Changes  of Steady States Using Mathematical Theory of Evidence,”   AIChE  J., 33, 1930-1932 (1987).

  3. Rao, R.R., and S. Narasimhan, “A Comparision of Techniques for Data  Reconciliation of Multicomponent  Processes,”  Ind. Eng. Chem. Res.,  35, 1362-1368 (1996).

  4. Maquin D., S. Narasimhan, and J. Ragot, “Data Validation with Unknown Variance Matrix,” Comput. Chem. Engng ., 23, S609-S612 (Jun 1999).

  5. Vachhani, P., R. Rengaswamy, V. Gangwal, and S. Narasimhan, ”Recursive estimation in Constrained Nonlinear Dynamical Systems,” AIChE J., 51 (3), 946-959 (Mar 2005).

  6. Ravi Kumar, V., S.R. Singh, M.O. Garg, and S. Narasimhan, “RAGE - A  Software for  Data  Reconciliation  and Gross  Error Detection,”  Proceedings of Second International Conference on FOCAPO (Eds. D.W.T. Rippin, J.C. Hale, and J.F. Davis), Colorado, USA,  429 (1994).

  7. Narasimhan, S., and S.L. Shah, “Model Identification and Error Covariance Matrix Estimation from Noisy Data using PCA,” Proceedings of 7th International Symposium on Advanced Control of Chemical Processes, Hong Kong, 567-572 (2004).

  8. Imtiaz, S.A., S.L. Shah, and S. Narasimhan, “Missing Data Treatment using Iterative PCA and Data Reconciliation,” Proceedings of 7th International Conference on Dynamics and Control of Process Systems (Eds. S.L. Shah and J.F. MacGregor), 2004.

  9. Han, Z., S.L. Shah, and S. Narasimhan, “Detection and Diagnosis of Data Reconciliation Problems in an Industrial Chemical Inventory System,” Proceedings of 7th International Conference on Dynamics and Control of Process Systems (Eds. S.L. Shah and J.F. MacGregor), 2004.

  10. Reddy, H. P., S. Narasimhan, and S.M. Bhallamudi, “Simulation and State Estimation of Transient Flow in Gas Pipeline Networks using Transfer Function Model,” I&EC Res., 45 (11), 3853-3863, 2006.

  11. Vachhani, P., S. Narasimhan and R. Rengaswamy, “Robust and Reliable Estimation via Unscented Recursive Nonlinear Dynamic Data Reconciliation,” J. Process Control,  16, 1075-1086, 2006.

  12. Bhatt, N.P., A. Mitna, and S. Narasimhan, “Multivariate Calibration of Non-Replicated Measurements for Heteroscedastic Errors,” Chemometr. Intell. Lab.  85, 70-81, 2007.

  13. Narasimhan, S. and S. L. Shah, “Model Identification and Error Covariance Matrix Estimation from Noisy Data using PCA,” Control Eng. Practice, 16, 146-155, 2008.

  14. Mohan Kumar, S. Narasimhan, and S.M. Bhallamudi, “State Estimation in Water Distribution Networks using Graph-Theoretic Reduction Strategy,” J. Water Res. Planning and Mgmt., 134 (5), 395-403, 2008.

  15. Narasimhan, S., and R. Rengaswamy, "Reply to Comments on Recursive Estimation in Constrained Nonlinear Dynamical Systems," AIChE J., 55 (4), 1080, 2009.

  16. Narasimhan, S., and R. Rengaswamy, "Reply to Comments on Robust and reliable estimation via unscented recursive nonlinear dynamic data reconciliation (URNDDR)," J.  Process Control, 19 (4) 719-721, 2009.

  1. Narasimhan, S., and R.S.H.  Mah,  “Generalized  Likelihood  Ratio Method for  Gross  Error  Identification,”   AIChE  J.,   33,  1514-1521 (1987).

  2.  Narasimhan, S., and R.S.H. Mah,  “Generalized  Likelihood  Ratios for Gross Error Identification in Dynamic Processes,”  AIChE  J., 34, 1321-1331 (1988).

  3.  Narasimhan, S., and R.S.H.  Mah,  “Treatment  of  General  Steady State Process Models  in  Gross  Error  Identification,”   Comput. Chem. Engng.,  13, 851-853 (1989).

  4.  Narasimhan, S., “Maximum Power Tests for  Gross  Error  Detection Using Likelihood Ratios,”  AIChE J.,  36, 1589-1591 (1990).

  5.  Narasimhan, S.,  and P. Harikumar, “The Treatment  of Bounds in Data Reconciliation  and Gross Error  Detection---I. The Bounded  Data Reconciliation Problem,”  Comput.  Chem. Engng.,  17, 1115-1120 (1993).

  6.  Harikumar, P.,  and S. Narasimhan, “The Treatment  of Bounds in Data  Reconciliation  and  Gross  Error  Detection---II.  Gross  Error Detection  Strategies,"   Comput. Chem.  Engng.,   17, 1121-1128 (1993).

  7. Gupta, G., and S. Narasimhan, “Application of Neural Networks for Gross Error Detection,”  Ind. Eng. Chem. Res.,  32, 1651-1657 (1993).

  8. Renganathan T, and S. Narasimhan, “A Strategy for Detection of Gross Errors in Nonlinear Processes,”  Ind Eng Chem Res , 38, 2391-2399 (Jun 1999).

  9. Mukherjee, J.,  and  S.  Narasimhan, “Leak  Detection in Networks of Pipelines by the Generalized Likelihood Ratio Method,”  Ind. Eng. Chem. Res,  35, 1886-1893 (1996).

  10. Prakash J, S.C. Patwardhan, and S. Narasimhan, “A supervisory approach to fault-tolerant control of linear multivariable systems,” Ind. Eng. Chem. Res., 41, 2270-2281 (May 2002.

  11. Prakash, J., S. Narasimhan, and S.C. Patwardhan, “Integrating Model Based Fault Diagnosis with Model Predictive Control,” I&EC Research (2005).

  12. Srinivasan, R., R. Rengaswamy, S. Narasimhan, and R. Miller, “Control Loop performance Assessment: A Hammerstein Model Approach for Stiction Diagnosis,” I&EC Research 44 (17), 6719-6728, 2005.

  13. Patwardhan, S.C., S. Manuja, S. Narasimhan, and S.L. Shah, “From Data to Diagnosis and Control using Generalized Orthonormal Basis Filters Part II: Model Predictive and Fault Tolerant Control,” J. Process Control, 16 (2), 157-175, 2006.

  14. Patwardhan, S.C., S. Manuja, S., S. Narasimhan, and S.L. Shah, “Online Diagnosis and Reconstruction of a Biased Sensor using State Observer Identified from Input-Output Data,” Proceedings of International Symposium on Advances Control of Industrial Processes, Kumamoto, Japan, 239-244 (2002).

  15.  Manuja, S., S. Narasimhan, and S.C. Patwardhan, “Isolation of Abrupt Changes in Unmeasured Disturbances using State Space Models Identified from Input-Output Data,” Proceedings of International Symposium on Process Systems Engineering and Control, Mumbai, INDIA, 157-162 (January 2003).

  16.  Vijayabaskar, R., and S. Narasimhan, “Fault tolerant Control of CSTR using Nonlinear State Estimation,” Proceedings of International Symposium on Process Systems Engineering and Control, Mumbai, INDIA, 346-352 (January 2003).

  17. Manuja, S., S.C. Patwardhan, and S. Narasimhan, “Fault Tolerant control using identified Models, : An Experimental Study,” Proceedings of International Conference on Intelligent Sensing and Remote Processing (Eds.),” Chennai, 460-465 (January 2004)

  18. Prakash, J., Vanchynathan, A.G.K., Padmavathi, G., S.C. Patwardhan, S. Narasimhan, and A. Jhunjhunwala, "Design of an Intelligent Control Network for Industrial Automation," Proceedings of National Symposium on Intelligent Measurement and Control (Eds. P. Kanagasabapathy, and R. Muthu), Chennai, India, 166-171 (2000).

  19. Prakash, J., S. Patwardhan, and S. Narasimhan, "Fault Tolerant Control of Continuous Stirred Tank Reactor," Proceedings of International Conference on Communications, Control and Signal Processing (Eds. A. Kumar and V.U. Reddy), Bangalore, India, 117-121, 2000.

  20. Vachhani, P., S. Narasimhan and R. Rengaswamy, “An Integrated Qualitative—Quantitative Hypothesis Driven Approach for Comprehensive Fault Diagnosis,” Chem. Eng. Res. Des.,  85, 1281-1294, 2007.

  21. Deshpande, A., S.C. Patwardhan, and  S. Narasimhan,  “Integrating fault diagnosis with nonlinear model  predictive control.”, In Assessment and Future Directions of Nonlinear Model Predictive Control, Findeisen, R., Allgower, F. Biegler, L. T. (Eds.), 2007, 513-522, Springer, Berlin.

  22. Seema, M. S.C. Patwardhan, S. Narasimhan, “Fault Diagnosis and Fault Tolerant Control using Reduced Order Models,” Can. J. Chem. Eng., 86 (4), 791-803, 2008.

  23. Manuja, S., S.C. Patwardhan, and S. Narasimhan, “Unknown Input Modeling and Robust Fault Diagnosis using Black Box Observers,” J. Process Control, 19 (1), 25-37, 2009.

  24. Deshpande, A.P., S.C. Patwardhan, and S. Narasimhan, "Intelligent State Estimation for Fault Tolerant Nonlinear Model Predictive Control," J. Process Control, 19 (2), 187-204, 2009.

  1. Ali,  Y.,  and  S.  Narasimhan,  “Sensor  Network  Design  for Maximizing  Reliability of  Linear Processes,”   AIChE  J., 39, 820-828 (1993).

  2. Ali, Y., and S. Narasimhan, “Redundant Sensor Network Design for Linear Processes,”  AIChE J.,  41, 2237-2249 (1995).

  3. Ali, Y., and S. Narasimhan, “Sensor Network Design for Maximizing Reliability of Bilinear Processes,” AIChE J., 42, 2563-2575 (1996).

  4. Sen S., S. Narasimhan and K. Deb, “Sensor Network Design of  Linear Processes Using Genetic Algorithms,” Comput. Chem. Engng, 22, 385-390 (1998).

  5. Bansal, P., Ali, Y., and S. Narasimhan, “Sensor Network Design in Linear Processes,” Proceedings of IFAC Conference on Integration of Process Design and Control (Eds. E. Zafiriou, and T. J. McAvoy), Maryland, USA, (1993).

  6. Mehta. R.K.C., and S. Narasimhan, “Evolutionary Synthesis of Heat Exchanger Networks,” Proceedings of Third ISHMT-ASME Heat and Mass Transfer Conference (Eds. G. Biswas,  S. Srinivasa Murthy, K. Muralidhar, and V.K. Dhir), Kanpur, India, 765 (1997).

  7. Narasimhan, S, “Recent Advances in Computer-Aided Process Design,” J. Energy, Heat and Mass Transfer, 19, 115-125 (1997).

  8. Varma, K.V.K., S. Narasimhan, and S.M. Bhallamudi, “A Reduced Successive Quadratic Optimization Method for Design of Water Distribution Systems,” J. Envir. Engrg., ASCE, 123, 381-388 (1997).

  9.  Naidu, B.J., S.M. Bhallamudi, and S. Narasimhan, “GVF Computation in Tree--Type Channel Networks,” J. Hydr. Engrg., ASCE, 123, 700-709 (1997).

  10. Viswanath, A., and S. Narasimhan, “Multi-objective Sensor Network Design using Genetic Algorithms,” Proceedings of 4th IFAC Workshop on On-line fault detection and supervision in the chemical process industries, Korea,  265-268 (June 2001).

  11. Mehta, R.K.C., S. K. Devalkar, and S. Narasimhan, “An optimization approach for evolutionary synthesis of heat exchanger networks,” Chemical Engineering Research & Design, 79, 143-150 (Mar 2001).

  12. Shivakumar, K and S. Narasimhan, “A Robust and Efficient NLP Formulation Using Graph Theoretic Principles for Synthesis of Heat Exchanger Networks,” Comput. Chem. Engng , 26 (11): 1517-1532 (Nov, 2002).