Practical Design and Application of Model Predictive Control is a self-learning resource for readers to learn how to design, tune, and deploy Model Predictive Control (MPC) using MATLAB and Simulink. This reference is one of the most detailed publications on how to design and tune MPC controllers. Examples presented range from double-Mass spring system, ship heading and speed control, robustness analysis through Monte-Carlo simulations, photovoltaic optimal control, and energy management of power-split and air-handling control. Readers will also learn how to embed the designed MPC controller in a real-time platform such as Arduino.
The selected problems are nonlinear and challenging, and serve as an excellent experimental, dynamic system to show the reader the capability of MPC. The step-by-step solutions of the problems are thoroughly documented to allow the reader to easily replicate the results. Furthermore, the MATLAB and Simulink codes for the solutions are available for free download on the MATLAB Central File Exchange.