How Can Robust Control of Nonlinear Systems be Achieved? Examining Optimization Techniques

Inhaltsverzeichnis (Table of Contents)

• CHAPTER 1
  • Introduction
  • Background

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This thesis focuses on the design of robust controllers for nonlinear systems using evolutionary optimization techniques and Linear Matrix Inequalities (LMIs). The work explores the limitations of classical control methods for nonlinear systems and investigates how feedback linearization, a technique for transforming nonlinear systems into linear ones, can be made more robust against uncertainties and disturbances. The thesis also examines the application of nonlinear disturbance observer-based control (NDOBC) and sliding mode control (SMC) for enhanced performance and robustness.

• Robust control of nonlinear systems
• Feedback linearization and its limitations
• Evolutionary optimization techniques for controller design
• Nonlinear disturbance observer-based control (NDOBC)
• Sliding mode control (SMC) for robustness and chattering reduction

Zusammenfassung der Kapitel (Chapter Summaries)

Chapter 1 provides an introduction to the challenges of controlling nonlinear systems and highlights the limitations of traditional linear control approaches. It introduces feedback linearization as a solution for transforming nonlinear systems into linear ones. The chapter also discusses the importance of robustness in feedback linearization and explores the concept of robust feedback linearization.

Schlüsselwörter (Keywords)

Nonlinear systems, robust control, feedback linearization, evolutionary optimization, LMI, disturbance observer, sliding mode control, chattering reduction, genetic algorithms.