MATLAB Integrated Toolbox for Optimal Control

This article introduces the Integrated Optimal Control Toolbox developed by Professor Xue Dingyu. It is a highly practical MATLAB toolbox designed to provide users with convenient tools for solving optimal control problems. The toolbox integrates various optimal control algorithms, including linear and nonlinear model predictive control (MPC), Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG), H-infinity control, and more. The implementation typically involves MATLAB's Control System Toolbox functions, with custom wrapper functions that simplify algorithm configuration and execution. Additionally, it provides practical utilities such as model parameter estimation using system identification techniques and state estimation through Kalman filter implementations, helping users better understand and solve optimal control problems. The toolbox architecture allows for seamless integration of custom control algorithms through standardized MATLAB function interfaces. Overall, this integrated toolbox serves as a highly practical solution for various optimal control problems, suitable for both academic research and industrial applications.