Publications

Abstract : An advanced control method, Model Predictive Control (MPC) has been widely used and well received in a wide variety of applications in process control. MPC utilizes an explicit process model to predict the future response of a process and solve a control problem with a finite horizon at each sampling instant. Model predictive control has proven to be a very effective controller design strategy over the last twenty years and has been widely used in process industry, such as oil refining, chemical engineering and metallurgy. A greater challenge for the controllers is to control an unstable system. In this work, a three tank interacting system has been used to implement Model Predictive Control for controlling the level of water in all the three tanks placed at the corners of an equilateral triangle with input, interaction and drain from each tank thus making the system a Multi-Input Multi-Output (MIMO). The appropriate model equations in the non-linear form have been formulated for the proposed system. The non-linear equations are linearized and a state space model was developed and implemented using MPC tool box of MATLAB. MPC simulation environment has been used to design the controller for the three tank interacting system and comparednbsp;the results under various operating conditions including the constraints. The MPC behavior has been analyzed for set point control of the level of water in three tanks by tuning the extent of interaction between the tanks through the openings of solenoid valves connecting the tanks./p