Abstract
This paper addresses the adaptive optimized fuzzy control for the uncertain nonlinear systems with preset tracking accuracy. Compared with the existing optimized backstepping control, this paper uses two \(C^n\)-class functions to construct the target controllers and the tracking error can converge to a pre-given range. Furthermore, the cost functions are re-developed in this paper, and the optimized performance indicator functions for each sub-system are explored to evaluate the control performance for the controlled system. Thus, the virtual optimized controllers and the actual optimized controller are constructed via the backstepping technique. It is demonstrated that each signal in the closed-loop system is semi-globally uniformly ultimately bounded. Finally, a comparative experiment of the numerical simulation further shows that the control strategy in this paper can effectively reduce control consumption.
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The data used to support the findings of this study are available from the corresponding author upon request.
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Funding
This work was supported in part by the National Natural Science Foundation of China under Grant 61603003; in part by the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China, under Grant ICT2022B39; in part by the Program for Academic Top Notch Talents of University Disciplines under Grant gxbjZD21; in part by the Anhui University Scientific Research Project-Outstanding Youth Project under Grant 2022AH020067.
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Wu, J., Wang, W. & Li, J. Adaptive Optimized Fuzzy Control of Uncertain Strict-Feedback Systems with Preset Tracking Accuracy. Int. J. Fuzzy Syst. 25, 2699–2711 (2023). https://doi.org/10.1007/s40815-023-01518-w
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DOI: https://doi.org/10.1007/s40815-023-01518-w