Suitable for advanced undergraduates and graduate students, this text introduces theoretical and practical aspects of adaptive control. It offers an excellent perspective on techniques as well as an active knowledge of key approaches. Readers will acquire a well-developed sense of when to use adaptive techniques and when other methods are more appropriate.
Starting with a broad overview, the text explores real-time estimation, self-tuning regulators and model-reference adaptive systems, stochastic adaptive control, and automatic tuning of regulators. Additional topics include gain scheduling, robust high-gain control and self-oscillating controllers, and suggestions for implementing adaptive controllers. Concluding chapters feature a summary of applications and a brief review of additional areas closely related to adaptive control.
Both authors are Professors at the Lund Institute of Technology in Sweden, and this text has evolved from their many years of research and teaching. Their insights into properties, design procedures, and implementation of adaptive controllers are complemented by the numerous examples, simulations, and problems that appear throughout the book.
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adaptation gain adaptive control adaptive systems adjustment algorithm amplitude applications assumed auto-tuning automatic tuning behavior block diagram Chapter closed-loop poles closed-loop system command signal computed constant continuous-time control design control law control problem control signal control systems controller parameters convergence covariance derived described determine Diophantine equation direct self-tuning discrete-time discussed disturbances dual control equilibrium error feedback feedforward Figure ﬁlter ﬁrst follows from Eq frequency gain scheduling given by Eq gives input signal introduce least-squares estimation limit cycle loop loss function Lyapunov Lyapunov function matrix minimum-variance controller MRAS nonlinear Notice obtained operator optimal P-matrix parameter estimates persistently exciting PID controllers pole placement polynomial properties recursive recursive least squares relay response robust sampling period Section self-tuning regulator shown in Fig shows simulation solution stability step step responses stochastic system in Example Theorem theory time-varying system transfer function unmodeled dynamics updating values variables variations