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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
(R) is integrated, and numerous examples and exercises are included
for each chapter. Associated MATLAB (R) code will be made
available.
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