Adaptive asymptotic tracking control for nonlinear systems with state constraints and input saturation

Le Wang, Wei Sun and Shun-Feng Su

Applied Mathematics and Computation, 2022, vol. 431, issue C

Abstract: In this study, an adaptive asymptotic tracking control scheme is designed for strict-feedback nonlinear systems with state constraints and input saturation. First of all, the asymmetric time-varying constraints on the states are realized by introducing the corresponding function transformations, thus the feasibility conditions are eliminated and the requirements of constrained boundary functions are relaxed. Meanwhile, to ensure that the system output asymptotically tracks the desired signal, a new nonlinear function of the tracking error is constructed which is different from other system states. Then, the saturation nonlinearity is approximated by using a smooth function, and an auxiliary system is introduced to compensate for the effect of the error function. During the design process, fuzzy logic systems and command filtered technique are applied to handle the uncertainties and the problem of complexity explosion in adaptive backstepping method, respectively. The proposed scheme guarantees that system states will not exceed the given asymmetric constraint boundaries and the tracking error can converge to zero asymptotically. Finally, the given simulation examples validate the effectiveness of the constructed strategy.

Keywords: Adaptive asymptotic tracking; State constraints; Input saturation; Command filtered technique (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:431:y:2022:i:c:s0096300322004167

DOI: 10.1016/j.amc.2022.127342

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