Robust Control Toolbox 3.5

Introduction

The Robust Control Toolbox provides tools for systematically factoring model uncertainty into your design to ensure consistent controller performance on the real plant. These tools let you quickly identify worst-case scenarios and automatically generate controllers with reduced sensitivity to parameter variations and modeling errors.

The toolbox extends the Control System Toolbox with tools that bridge classical control design methods and advanced robust control techniques. It includes algorithms to quantify uncertainty in your model, analyze its impact on control system performance, design robust controllers with guaranteed performance on the real plant, and reduce the complexity of plant and controller models. These algorithms are applicable to single-loop (SISO) and multi-loop (MIMO) control systems.

Key Features

• µ-analysis and LMI-based techniques for analyzing the robustness of MIMO control systems
• Algorithms for frequency-domain loop shaping of MIMO open-loop responses
• H and µ-synthesis techniques for robust control system design
• Approximation algorithms for model order reduction
• General-purpose LMI solvers (feasibility, minimization of linear objectives, and generalized eigenvalue minimization)