Delay-Adaptive Linear Control

Yang Zhu · Miroslav Krstic

2020年4月 · Princeton University Press

電子書

352

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關於這本電子書

Actuator and sensor delays are among the most common dynamic phenomena in engineering practice, and when disregarded, they render controlled systems unstable. Over the past sixty years, predictor feedback has been a key tool for compensating such delays, but conventional predictor feedback algorithms assume that the delays and other parameters of a given system are known. When incorrect parameter values are used in the predictor, the resulting controller may be as destabilizing as without the delay compensation.

Delay-Adaptive Linear Control develops adaptive predictor feedback algorithms equipped with online estimators of unknown delays and other parameters. Such estimators are designed as nonlinear differential equations, which dynamically adjust the parameters of the predictor. The design and analysis of the adaptive predictors involves a Lyapunov stability study of systems whose dimension is infinite, because of the delays, and nonlinear, because of the parameter estimators. This comprehensive book solves adaptive delay compensation problems for systems with single and multiple inputs/outputs, unknown and distinct delays in different input channels, unknown delay kernels, unknown plant parameters, unmeasurable finite-dimensional plant states, and unmeasurable infinite-dimensional actuator states.

Presenting breakthroughs in adaptive control and control of delay systems, Delay-Adaptive Linear Control offers powerful new tools for the control engineer and the mathematician.

關於作者

Yang Zhu is a postdoctoral researcher in control theory and engineering at Tel Aviv University. Miroslav Krstic is distinguished professor of mechanical and aerospace engineering at the University of California, San Diego, where he also serves as senior associate vice chancellor for research. He is the coauthor of many books, including Nonlinear and Adaptive Control Design (Wiley) and Adaptive Control of Parabolic PDEs (Princeton).