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Modern Anti-windup SynthesisControl Augmentation for Actuator Saturation$
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Luca Zaccarian and Andrew R. Teel

Print publication date: 2011

Print ISBN-13: 9780691147321

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691147321.001.0001

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Linear M RAW Synthesis

Linear M RAW Synthesis

(p.174) Chapter Seven Linear M RAW Synthesis
Modern Anti-windup Synthesis

Luca Zaccarian

Andrew R. Teel

Princeton University Press

This chapter deals with linear model recovery anti-windup (MRAW) synthesis. The MRAW structure permits recovering information about the unconstrained response, so that unconstrained response recovery is possible through the extra degree of freedom represented by the unspecified compensation signal. The stability and performance properties induced by MRAW on the closed loop depend on the choice of the feedback signal. In discussing linear MRAW synthesis, the chapter refers to suitable state–space representations of the plant and of the anti-windup compensator dynamics. It first considers anti-windup synthesis algorithms based on linear matrix inequalities (LMIs) for which global stability and performance are guaranteed before describing LMI-based synthesis algorithms for regional stability and performance.

Keywords:   linear model recovery anti-windup, unconstrained response, closed loop, feedback signal, state–space representation, anti-windup compensator, anti-windup synthesis, linear matrix inequalities, global stability, regional stability

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