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Design of model predictive control for nonlinear process

The objective of this paper is to design and implement the model predictive controller (MPC) for a nonlinear process. In this study, the two interacting conical frustum tank level (TICFTL) process is considered and the state space model is developed from the experimental data. The MPC controller is designed based on the state space model. The process of design and implementation of MPC controller in the Matlab & Simulink environment is detailed. The superiority of servo and regulatory controller performances confirms that the MPC is one of the best controllers for the nonlinear process.