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Controller Tuning Optimization Methods for Multi-Constraints and Nonlinear Systems

A Metaheuristic Approach

  • Book
  • © 2021

Overview

Authors:
  1. Maude Josée Blondin

    1. Département Génie Électr. & Inform., Université de Sherbrooke, Sherbrooke, Canada

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  • Overviews classical controller tuning methods, applications, and limitations
  • Features state-of-the-art optimization algorithms applied to controller tuning with performance comparisons
  • Provides insights for developing new optimization techniques

Part of the book series: SpringerBriefs in Optimization (BRIEFSOPTI)

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Table of contents (4 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Optimization Algorithms in Control Systems

    • Maude Josée Blondin
    Pages 1-9

  3. Controller Tuning by Metaheuristics Optimization

    • Maude Josée Blondin
    Pages 11-51

  4. Case Studies

    • Maude Josée Blondin
    Pages 53-89

  5. Future Direction and Research Trends

    • Maude Josée Blondin
    Pages 91-101
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Keywords

About this book

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.

Authors and Affiliations

  • Département Génie Électr. & Inform., Université de Sherbrooke, Sherbrooke, Canada

    Maude Josée Blondin

About the author

​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.

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