2012
DOI: 10.1002/rnc.2879
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Robust H ∞  control via a stable decentralized nonlinear output feedback controller

Abstract: SUMMARYThis paper presents a new method to construct a decentralized nonlinear robust H ∞  controller for a class of large‐scale nonlinear uncertain systems. The admissible uncertainties and nonlinearities in the system satisfy integral quadratic constraints and global Lipschitz conditions, respectively. The decentralized controller, which is required to be stable, is capable of exploiting known nonlinearities and interconnections between subsystems without treating them as uncertainties. Instead, additional u… Show more

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Cited by 6 publications
(1 citation statement)
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“…A decentralized adaptive controller is proposed for a class of uncertain interconnected systems with unknown modeling errors and interactions (Cai et al, 2022), where the proposed controller can ensure that all closed-loop system signals are bounded by using backstepping methods. Harno and Petersen (2014) demonstrate that the decentralized controller can exploit known nonlinearities and interconnections between subsystems without treating them as uncertainties. A decentralized state estimator is proposed by Liu and Yu (2018) for spatially interconnected systems with arbitrary connection relations, and an optimization problem based on linear matrix inequalities (LMIs) is constructed for the computations of improved subsystem parameter matrices.…”
Section: Introductionmentioning
confidence: 99%
“…A decentralized adaptive controller is proposed for a class of uncertain interconnected systems with unknown modeling errors and interactions (Cai et al, 2022), where the proposed controller can ensure that all closed-loop system signals are bounded by using backstepping methods. Harno and Petersen (2014) demonstrate that the decentralized controller can exploit known nonlinearities and interconnections between subsystems without treating them as uncertainties. A decentralized state estimator is proposed by Liu and Yu (2018) for spatially interconnected systems with arbitrary connection relations, and an optimization problem based on linear matrix inequalities (LMIs) is constructed for the computations of improved subsystem parameter matrices.…”
Section: Introductionmentioning
confidence: 99%