Yu Li Robust Control Design Example with LMI Approach

This article presents Yu Li's robust control design methodology through a practical example program based on Linear Matrix Inequality (LMI) approach, offering a detailed case study of robust controller design for dynamical systems. The implementation typically involves defining system uncertainties using norm-bounded parameters and formulating stability conditions as LMI constraints. Key computational steps include constructing Lyapunov functions, solving convex optimization problems using MATLAB's LMI toolbox functions like lmivar for variable declaration and feasp for feasibility solutions, and validating controller performance through robustness analysis. Robust control represents a crucial branch in control theory that ensures system stability and performance maintenance under uncertain operating conditions. This methodology finds widespread applications in modern engineering domains including aerospace systems, automotive industries, and robotic control systems. Mastering robust control theory and design techniques is therefore essential for control engineers. The exemplary program from Yu Li's robust control design serves as valuable learning material, helping readers deepen their understanding of robust control concepts and applications while providing a practical design template for real-world implementations.