Control systems : classical, modern, and AI-based approaches
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Bibliographic Information
Control systems : classical, modern, and AI-based approaches
CRC Press, c2020
- : hbk
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Includes bibliographical references and index
Description and Table of Contents
Description
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 (R) is integrated, and numerous examples and exercises are included for each chapter. Associated MATLAB (R) 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 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
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