Quasilinear control: Performance analysis and design of feedback systems with nonlinear sensors and actuators

Shinung Ching; Yongsoon Eun; Cevat Gokcek; Pierre T. Kabamba; Semyon M. Meerkov

doi:10.1017/CBO9780511976476

Quasilinear control: Performance analysis and design of feedback systems with nonlinear sensors and actuators

Shinung Ching, Yongsoon Eun, Cevat Gokcek, Pierre T. Kabamba, Semyon M. Meerkov

Research output: Book/Report › Book › peer-review

28 Scopus citations

Abstract

This is a textbook and reference for readers interested in quasilinear control (QLC). QLC is a set of methods for performance analysis and design of linear plant or nonlinear instrumentation (LPNI) systems. The approach of QLC is based on the method of stochastic linearization, which reduces the nonlinearities of actuators and sensors to quasilinear gains. Unlike the usual - Jacobian linearization - stochastic linearization is global. Using this approximation, QLC extends most of the linear control theory techniques to LPNI systems. A bisection algorithm for solving these equations is provided. In addition, QLC includes new problems, specific for the LPNI scenario. Examples include Instrumented LQR/LQG, in which the controller is designed simultaneously with the actuator and sensor, and partial and complete performance recovery, in which the degradation of linear performance is either contained by selecting the right instrumentation or completely eliminated by the controller boosting.

Original language	English
Publisher	Cambridge University Press
Number of pages	282
Volume	9781107000568
ISBN (Electronic)	9780511976476
ISBN (Print)	9781107000568
DOIs	https://doi.org/10.1017/CBO9780511976476
State	Published - Jan 1 2010

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abstract = "This is a textbook and reference for readers interested in quasilinear control (QLC). QLC is a set of methods for performance analysis and design of linear plant or nonlinear instrumentation (LPNI) systems. The approach of QLC is based on the method of stochastic linearization, which reduces the nonlinearities of actuators and sensors to quasilinear gains. Unlike the usual - Jacobian linearization - stochastic linearization is global. Using this approximation, QLC extends most of the linear control theory techniques to LPNI systems. A bisection algorithm for solving these equations is provided. In addition, QLC includes new problems, specific for the LPNI scenario. Examples include Instrumented LQR/LQG, in which the controller is designed simultaneously with the actuator and sensor, and partial and complete performance recovery, in which the degradation of linear performance is either contained by selecting the right instrumentation or completely eliminated by the controller boosting.",

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AU - Meerkov, Semyon M.

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Quasilinear control: Performance analysis and design of feedback systems with nonlinear sensors and actuators

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