Controller Tuning Optimization Methods for Multi-Constraints and Nonlinear Systems

A Metaheuristic Approach
1. Auflage 2021
ISBN: 978-3-030-64540-3
Verlag: Springer International Publishing

Buch, Englisch, 101 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 184 g

Reihe: SpringerBriefs in Optimization

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.

Zielgruppe

Research

Autoren/Hrsg.

Blondin, Maude Josée

Fachgebiete

• Mathematik | Informatik Mathematik Mathematische Analysis Differentialrechnungen und -gleichungen
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik

Inhaltsverzeichnis

1 Optimization algorithms in control systems.- 2 Controller tuning by metaheuristics optimization.- 3 Case studies.- 4 Future direction and research trends.

Über Autor(innen)

Maude Blondin is an assistant professor at the Université de Sherbrooke in Canada. She graduated with a Ph.D. in Electrical Engineering from the Université du Québec à Trois-Rivières,  where she obtained the prestigious Vanier Canada Graduate Scholarship. Her doctoral research was on computational intelligence methods and soft computing techniques applied to control engineering. Afterward, Dr. Blondin did postdoctoral research in the mechanical and aerospace engineering department at the University of Florida. She expanded her research interests to multiobjective optimization applied to multiagent control strategies. Her current research is driven by developing distributed multiobjective optimization algorithms based on exploring the Pareto Front and soft computing methods for multiagent systems. These algorithms are used in many applications ranging from managing energy to military uses to swarm robotics.