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Adaptive Quantized Control for Uncertain Nonlinear Systems with Asymmetric Fuzzy Dead Zones

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Abstract

This paper aims at the tracking control for a class of nonstrict-feedback nonlinear systems with input quantization, asymmetric fuzzy dead zones and unknown control directions. First, a useful coordinate transformation is firstly given such that the problem caused by the unknown control coefficients is figured out, and then the researched system is transformed into an equivalent system. Second, with the combination of the nonlinear decomposition of an asymmetric hysteresis quantizer and a simplified asymmetric dead zone model obtained by adopting the integrated design algorithm, a feasible connection between system input and control signal is established. Then, the difficult control issue that results from the coexistence of the asymmetric hysteresis quantization and asymmetric fuzzy dead zone is overcome. Third, the fuzzy logic systems (FLSs) are applied to approximate the unknown nonlinear functions. By introducing a smooth function, a novel adaptive fuzzy control scheme is proposed via backstepping technique. It is proved that the integrated fuzzy controller can make all the signals of the closed-loop system bounded and make the tracking error as small as possible. Finally, simulation results are shown to demonstrate the effectiveness of our proposed algorithm.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 62103243, 52234005), the Shandong Provincial Natural Science Foundation (No. ZR2020QF074), and the Project funded by China Postdoctoral Science Foundation (No. 2022M721974).

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Correspondence to Hang Su.

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Su, H., Zhang, Q. Adaptive Quantized Control for Uncertain Nonlinear Systems with Asymmetric Fuzzy Dead Zones. Int. J. Fuzzy Syst. 26, 60–72 (2024). https://doi.org/10.1007/s40815-023-01575-1

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