Introduction
MATLABSolutions demonstrate In this task we are going to designModel Predictive Control (MPC) is one of the most popularly use advanced control techniques since it can be used in a multivariable system and also has the ability to handle explicit constraints. The objective of this project is creating, installing, and analyzing an MPC controller in a state-space environment with a given system dynamics. The main target is to carry out the coordination and control with the constraints and achieving the desired performance.
Methodology
Steps in the development of MPC system comprised of some critical operations to get acceptable control and to stick to constraints during system operation. The model started by mapping the matrices of A, B, E and C. In between, the process was discretized by use of a sampling time of 0.1 seconds to allow the implementation of MPC model.The MPC controller was constructed with a 2 control and 10 prediction steps horizon, which was enough both for accuracy and for the computational complexity (Rodriguez et al., 2021). Considering constraint handling and the requisite constraints for input and output variables as safety measures were an integral part of the design whose primary objective was to ensure safe operation. Rates of manipulated variables, outputs variables, and constraint relaxation were calculated and evaluated.