Suitable for a semester course and ideal for a two-semester course! This state-of-the-art text illustrates the analysis, behavior, and design of linear control systems using classical, modern, and advanced control techniques—covering recent methods in system identification and optimal, digital, adaptive, robust, and fuzzy control, as well as stability, controllability, observability, pole placement, state observers, input-output decoupling, and model matching. Detailing the analysis of linear time-invariant systems using differential equations, transfer function, impulse response, and state-space equations, Modern Control Engineering presents
an overview of classical control engineering
Nyquist, Bode, and Nichols diagrams, and root locus, compensators, and three term controllers
modern and advanced engineering techniques for improved performance of control systems
system identification
discrete-time adaptive control using the gradient method, model reference adaptive control, and self-tuning regulators
robust stability and Kharitonov’s theorem
With nearly 3000 helpful equations, Modern Control Engineering is a valuable text for upper-level undergraduate and graduate students taking courses in control engineering design and applications.
Classical Control
Introduction to Automatic Control Systems
Mathematical Background
Mathematical Models of Systems
Classical Time-Domain Analysis of Control Systems
State-Space Analysis of Control Systems
Stability
The Root Locus Method
Frequency Domain Analysis
Classical Control Design Methods
Modern Control
State-Space Design Methods
Optimal Control
Digital Control
System Identification >
Adaptive Control
Robust Control
Fuzzy Control
Appendix A: Laplace Transform Tables
Appendix B: The Z-Transform
Appendix C: Z-Transform Tables
Index
