2016
DOI: 10.1002/rnc.3680
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Nonlinear robust state feedback control system design for nonlinear uncertain systems

Abstract: Summary This paper presents a systematic approach to the design of a nonlinear robust dynamic state feedback controller for nonlinear uncertain systems using copies of the plant nonlinearities. The technique is based on the use of integral quadratic constraints and minimax linear quadratic regulator control, and uses a structured uncertainty representation. The approach combines a linear state feedback guaranteed cost controller and copies of the plant nonlinearities to form a robust nonlinear controller with … Show more

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Cited by 4 publications
(2 citation statements)
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“…A comprehensive control scheme should consider both the robustness and the quality response of the considered systems (e.g., control effort minimization, settling time modification, and so forth). In this regard, several control approaches have been presented for making nonlinear systems robust against matched uncertainties 1‐7 and mismatched uncertainties, 8‐13 which are not in the range space of the input matrix. Due to their unique features, designing a controller that be able to optimally and robustly manage nonlinear systems subjected to mismatched uncertainties has been the desire of researchers.…”
Section: Introductionmentioning
confidence: 99%
“…A comprehensive control scheme should consider both the robustness and the quality response of the considered systems (e.g., control effort minimization, settling time modification, and so forth). In this regard, several control approaches have been presented for making nonlinear systems robust against matched uncertainties 1‐7 and mismatched uncertainties, 8‐13 which are not in the range space of the input matrix. Due to their unique features, designing a controller that be able to optimally and robustly manage nonlinear systems subjected to mismatched uncertainties has been the desire of researchers.…”
Section: Introductionmentioning
confidence: 99%
“…The control of nonlinear uncertain systems subject to physical constraints on both input and state is undoubtedly a challenging and important issue, involving either stabilization or tracking problems. To cope with this challenge, well‐known systematic nonlinear control methods such as feedback linearization and constructive Lyapunov‐based methods lead to very elegant solutions, but they often rely on a complicated design procedure that does not scale well to large systems, and they cannot handle constraints easily or in a systematic manner. Based on this, the concept of optimal control and in particular the receding horizon control (RHC) approach appears to be an attractive alternative since the complexity of the control design only increases moderately with the size and complexity of the system.…”
Section: Introductionmentioning
confidence: 99%