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Implementation-and-comparison-of-Advanced-process-control-to-stirred-tank-mixing-process

This is an implementation of Linear Quadratic Regulator (LQR), Minimum Principle and Model Predictive Control(MPC) to stirred tank mixing process. The repository contains the MATLAB code and a detailed report explaining the implementation. This report was submitted to fulfill the course requirement of the course CHE 694: Optimal Control in the Department of Chemical and Materials Engineering, University of Alberta.

Folder Information:

  • LQR : Contains the implimentation of Linear Quadratic Regulator(Implimentation) with lenearized system equation around a fix steady state.
  • Nonlinear_LQR : Contains the implimentation of LQR with actual non-linear system equations.
  • MINIMUM_PRINCIPLE : Contains the MATLAB code for implimentation of Minimum Principle with actual non-linear system equations with terminal time t_f = 8.
  • MPC : It has two sub-folders, Approch1 - with long prediction horizon and Approch2 - with terminal constraint.

Please refer to Report.pdf for the detailed information.

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Implementation of Linear Quadratic Regulator (LQR), Minimum Principle and Model Predictive Control(MPC) to stirred tank mixing process

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