Robust Control Systems with Genetic Algorithms

This text links genetic algorithms (GAs) and the design of robust control systems. After laying a foundation in the basics of GAs and genetic programming, it demonstrates the power of these tools for developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure control. It also explores the use of hybrid approaches that incorporate fuzzy logic into designs for intelligent control systems. The authors consider a variety of applications, such as robotic manipulators, flexible links, and jet engines, and illustrate a multi-objective GA approach using a case study.

Jamshidi, Mo; Krohling, Renato A.; dos S. Coelho, Leandro; Fleming, Peter J.

Genetic Algorithms. Optimal Robust Control. Methods for Controller Design Using Genetic Algorithms. Predictive and Structure Variable Control. Design Methods and Results. Tuning Fuzzy Logic Controllers for Robust Control Design. GA-Fuzzy Hierarchical Control Design Approach. Autonomous Robot Navigation through Fuzzy-Genetic Programming. Robust Control Systems Design: A Hybrid H-Infinity/Multi-Objective Optimization Approach. Appendices.