Control Systems: Classical, Modern, and AI-Based Approaches, 1st Edition (Hardback) book cover

Control Systems

Classical, Modern, and AI-Based Approaches, 1st Edition

By Jitendra R. Raol, Ramakalyan Ayyagari

CRC Press

678 pages | 438 B/W Illus.

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Hardback: 9780815346302
pub: 2019-07-31
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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.

Table of Contents

Section I: Linear and Nonlinear Control

1 Linear Systems and Control

2 Nonlinear Systems

3 Nonlinear Stability Analysis

4 Nonlinear Control Design

Appendix IA Performance error criteria

Appendix IB Table of Laplace Transforms

Appendix IC Describing function analysis for a model with a saturation nonlinearity

Appendix ID An iterative control design process

Exercises (For Section I)

References (For Section I)

Section II: Optimal and H-Infinity Control

5. Optimization-extremization of cost function

Appendix 5A Conditions in calculus of variation

6. Optimal control

Appendix 6A More topics of optimal control

7. Model predictive control

Appendix 7A Certain basic aspects of MPC and illustrative examples

Appendix 7B MPC Illustrative examples

8. Robust control

Appendix 8A Aspect of robustness and robust control with examples

Appendix IIA State space formulations

Appendix IIB Signal and system norms and performance indices

Appendix IIC Illustrative examples

Exercises (For Section II)

References (For Section II)

Section III: Digital and adaptive control

9. Discrete-time control system

Appendix 9A Some basic results of sampled data and digital control systems

10. Design of discrete time control systems

11. Adaptive control

Appendix 11A STC model structures for system identification and parameter estimation

Appendix 11B Sliding mode control

Appendix 11C Difficulties with adaptive control and their resolutions

12. Computer controlled systems

Appendix III Illustrative examples

Exercises (For Section III)

References (For Section III)

Section IV: Intelligent Control

13 Introduction

14 ANN Based Control Systems

Appendix 14A Adaptive neuro control

Appendix 14B Neural network based fault tolerant control: Lyapunov stability analysis

15. Fuzzy Control Systems

Appendix 15A Fuzzy logic in flight control-Gain scheduling

Appendix 15B Interval type 2 fuzzy logic (IT2FL) based pilot’s situation assessment

16 Nature Inspired Optimization for Controller Design

Appendix 16A Genetic algorithm based tuning of PI controllers

Appendix 16B Helicopter control design process using genetic algorithm

Appendix IVA Artificial intelligence, intelligent systems, and intelligent control

Exercises (For Section IV)

References (For Section IV)

Section V: System theory and control related topics

Appendix A Controllability, observability, identifiability, and estimability

Appendix B Stochastic processes and stochastic calculus-Brief treatment

Appendix C Lyapunov stability theory results

Appendix D Game theory and decentralized/centralized control

Appendix E Examples of control of dynamic systems

Appendix F Examples of aircraft control

About the Authors

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.

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