Introduction

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

doi:10.1017/CBO9780511976476.002

1 - Introduction

Published online by Cambridge University Press: 01 June 2011

ShiNung Ching ,

Yongsoon Eun ,

Cevat Gokcek ,

Pierre T. Kabamba and

Semyon M. Meerkov

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ShiNung Ching: Affiliation:
Massachusetts Institute of Technology
Yongsoon Eun: Affiliation:
Xerox Center for Research and Technology
Cevat Gokcek: Affiliation:
Michigan State University
Pierre T. Kabamba: Affiliation:
University of Michigan
Semyon M. Meerkov: Affiliation:
University of Michigan

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Summary

Motivation: This chapter is intended to introduce the class of systems addressed in this volume – the so-called Linear Plant/Nonlinear Instrumentation (LPNI) systems – and to characterize the control methodology developed in this book – Quasilinear Control (QLC).

Overview: After introducing the notions of LPNI systems and QLC and listing the problems addressed, the main technique of this book – the method of stochastic linearization – is briefly described and compared with the usual, Jacobian, linearization. In the framework of this comparison, it is shown that the former provides a more accurate description of LPNI systems than the latter, and the controllers designed using the QLC result, generically, yield better performance than those designed using linear control (LC). Finally, the content of the book is outlined.

Linear Plant/Nonlinear Instrumentation Systems and Quasilinear Control

Every control system contains nonlinear instrumentation – actuators and sensors. Indeed, the actuators are ubiquitously saturating; the sensors are often quantized; deadzone, friction, hysteresis, and so on are also encountered in actuator and sensor behavior.

Typically, the plants in control systems are nonlinear as well. However, if a control system operates effectively, that is, maintains its operation in a desired regime, the plant may be linearized and viewed as locally linear. The instrumentation, however, can not: to reject large disturbances, to respond to initial conditions sufficiently far away from the operating point, or to track large changes in reference signals – all may activate essential nonlinearities in actuators and sensors, resulting in fundamentally nonlinear behavior.

Type: Chapter
Information: Quasilinear Control
Performance Analysis and Design of Feedback Systems with Nonlinear Sensors and Actuators
, pp. 1 - 19

DOI: https://doi.org/10.1017/CBO9780511976476.002 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2010

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