1st Edition

Control Systems Classical, Modern, and AI-Based Approaches

    668 Pages 438 B/W Illustrations
    by CRC Press

    Control Systems: Classical, Modern, and AI-Based Approaches provides a broad and comprehensive study of the principles, mathematics, and applications for those studying basic control in mechanical, electrical, aerospace, and other engineering disciplines. The text builds a strong mathematical foundation of control theory of linear, nonlinear, optimal, model predictive, robust, digital, and adaptive control systems, and it addresses applications in several emerging areas, such as aircraft, electro-mechanical, and some nonengineering systems: DC motor control, steel beam thickness control, drum boiler, motional control system, chemical reactor, head-disk assembly, pitch control of an aircraft, yaw-damper control, helicopter control, and tidal power control. Decentralized control, game-theoretic control, and control of hybrid systems are discussed. Also, control systems based on artificial neural networks, fuzzy logic, and genetic algorithms, termed as AI-based systems are studied and analyzed with applications such as auto-landing aircraft, industrial process control, active suspension system, fuzzy gain scheduling, PID control, and adaptive neuro control. Numerical coverage with MATLAB® is integrated, and numerous examples and exercises are included for each chapter. Associated MATLAB® code will be made available.

    Section I: Linear and Nonlinear Control

    1. Linear Systems and Control

    2. Nonlinear Systems

    3. Nonlinear Stability Analysis

    4. Nonlinear Control Design

    Section II: Optimal and H-Infinity Control

    5. Optimization-Extremization of Cost Function

    6. Optimal Control

    7. Model Predictive Control

    8. Robust Control

    Section III: Digital and Adaptive Control

    9. Discrete Time Control Systems

    10. Design of Discrete Time Control Systems

    11. Adaptive Control

    12. Computer-Controlled Systems

    Section IV: AI-Based Control

    13. Introduction to AI-Based Control

    14. ANN-Based Control Systems

    15. Fuzzy Control Systems

    16. Nature Inspired Optimization for Controller Design

    Section V: System Theory and Control Related Topics

    Biography

    Jitendra R. Raol, PhD, is Emeritus Professor at the M. S. Ramaiah Institute of Technology in Bangalore, India. He previously served at the National Aerospace Laboratories (NAL) as Scientist-G and Head of the Flight Mechanics and Control Division (FMCD). He is a fellow of the IEE (UK), a senior member of the IEEE (US), a life-fellow of the Aeronautical Society of India, and a life member of the System Society of India. He has guided nearly a dozen doctoral research scholars and is a reviewer of many international journals.

    Ramakalyan Ayyagari, PhD, is with the Department of Instrumentation and Control Engineering at the National Institute of Technology—a deemed University, Tiruchirappalli, India. He earned a master’s at Andhra University, India, and a PhD at the Indian Institute of Technology, Delhi. Dr. Ayyagari’s areas of specialty include cyber physical systems, network flow control, modeling and control of big data systems, and path planning.