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I am working on MODEL PREDICTIVE CONTROL AND IDENTIFICATION for my M.Tech project. MPC is from that family of controllers in which there is a direct use of an explicit and separately identifiable model. Control design methods based on the MPC concept have found wide acceptance in industrial applications and have been studied by academia. The reason for such popularity is the ability of MPC designs to yield high performance control systems capable of operating without expert intervention for long periods of time. MPCI obtains sufficient model information on a process under constrained MPC, while minimally disturbing that process. To select a process input at each time step, MPCI solves a constrained optimization problem on-line with respect to process input values over a finite moving horizon. The project aimed at the design of Model Predictive Control with simultaneous Model Identification of a Distillation Column Setup housed in Chemical Engineering Department. My guide prof. Ravindra Gudi is an associate professor in Chemical Engineering Department, IIT Bombay. His research interests include Process Identification and Control, Statistical Methods and Biochemical Engineering. For more details about my work, I request to download my first stage and second stage report.