Controller Tuning Optimization Methods for Multi-Constraints and Nonlinear Systems: A Metaheuristic Approach (SpringerBriefs in Optimization)

✍ Scribed by Maude Josée Blondin

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 107
• Category: Library

✦ Synopsis

This book covers controller tuning techniques from conventional to new optimization methods for diverse control engineering applications. Classical controller tuning approaches are presented with real-world challenges faced in control engineering. Current developments in applying optimization techniques to controller tuning are explained. Case studies of optimization algorithms applied to controller tuning dealing with nonlinearities and limitations like the inverted pendulum and the automatic voltage regulator are presented with performance comparisons. Students and researchers in engineering and optimization interested in optimization methods for controller tuning will utilize this book to apply optimization algorithms to controller tuning, to choose the most suitable optimization algorithm for a specific application, and to develop new optimization techniques for controller tuning.

✦ Table of Contents

Preface
Acknowledgments
Contents
1 Optimization Algorithms in Control Systems
1.1 Introduction to Control System
1.2 Control Design Challenges
1.3 Optimization-Based Approach for Controllers Tuning
References
2 Controller Tuning by Metaheuristics Optimization
2.1 Historical Evolution of Metaheuristics
2.2 Metaheuristics Survey
2.3 Metaheuristics Common Principles
2.4 Simulated Annealing
2.5 Genetics Algorithm
References
3 Case Studies
3.1 Inverted Cart-Pendulum
3.1.1 Model of the Inverted Cart-Pendulum and its Controllers
3.1.1.1 Controller Structures
3.1.2 Controller Structure Optimization
3.1.3 Simulation Results
3.1.4 Discussion
3.2 AVR System
3.2.1 Model of the AVR System and its Controllers
3.2.2 Simulation Results
3.2.3 Discussion
3.3 Conclusion
References
4 Future Direction and Research Trends
4.1 Algorithm Contributions and Assessments
4.2 Recommendation for Future Research
4.3 Hybrid Metaheuristics
4.3.1 Hybrid Algorithms: Controller Tuning
4.4 Conclusion
References