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Adaptive Fuzzy Output-Feedback Tracking Control for Nonlinear Time-Varying State-Constrained Systems Without the Feasibility Condition

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Abstract

This paper investigates an adaptive fuzzy tracking controller for uncertain strict-feedback nonlinear systems suffering from asymmetric time-varying state constraints, unmeasured states, and unknown external disturbances. Firstly, a state observer with a simplified structure is constructed to approximate the unavailable system states based on fuzzy logic systems. The difficulties caused by time-varying state constraints are effectively addressed in a direct approach via the nonlinear state-dependent functions. Compared to the classical barrier Lyapunov functions-based (BLFs-based) method, the strict condition imposed on the virtual controller is eliminated, which significantly enhances the applicability of the controller in practical systems. Meanwhile, to handle the issue of “explosion of complexity,” a novel adaptive fuzzy tracking control technique is proposed by using the sliding-mode differentiator. Finally, rigorous stability analysis is employed to verify that the error between the system output signal and the reference signal can converge to an arbitrarily small set around the origin, and all closed-loop signals are bounded without time-varying state constraints violation. The effectiveness of the theoretical result is further illustrated by two simulation examples.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant Nos. 62373229 and 61973198, and China Scholarship Council under Grant No. CSC202208370123.

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Authors and Affiliations

  1. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, 266590, China

    Xiaoning Lv, Wei Wei & Weihai Zhang

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  1. Xiaoning Lv
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  2. Wei Wei
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  3. Weihai Zhang
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Correspondence to Weihai Zhang.

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Lv, X., Wei, W. & Zhang, W. Adaptive Fuzzy Output-Feedback Tracking Control for Nonlinear Time-Varying State-Constrained Systems Without the Feasibility Condition. Int. J. Fuzzy Syst. 26, 1233–1246 (2024). https://doi.org/10.1007/s40815-023-01663-2

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  • DOI: https://doi.org/10.1007/s40815-023-01663-2

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