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State Observer-Based Composite Adaptive Fault-Tolerant Fuzzy Control for Uncertain Nonlinear Systems with Quantized Inputs

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Abstract

This work researches the issue of adaptive fault-tolerant fuzzy tracking control for a class of nonlinear systems in strict-feedback form with quantized inputs. The fuzzy logic systems are utilized to approximate unknown functions, and a fuzzy state observer is built to estimate the unavailable states. Meanwhile, an improved hysteresis quantizer is introduced to achieve the quantized inputs for saving communication resources. To improve the approximation capacities of fuzzy logic systems, the compensated tracking errors and the prediction errors are used to construct the adaptive laws parameters. Furthermore, a composite adaptive fault-tolerant fuzzy control strategy is developed, which can guarantee proper operations of the systems when encountering actuator faults, and overcome the issue of “explosion of complexity” in the backstepping approach. It is strictly demonstrated that the system output can follow a desired signal within a small error zone and all signals of the closed-loop system are bounded. Finally, the simulation results are given to confirm the validity of the presented control strategy.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China, under Grant 62203064.

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Authors and Affiliations

  1. College of Control Science and Engineering, Bohai University, Jinzhou, 121013, Liaoning, China

    ZiXuan Huang

  2. School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, China

    Ben Niu

  3. College of Mathematical Science, Bohai University, Jinzhou, 121013, Liaoning, China

    Ning Zhao

  4. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024, Liaoning, China

    Xudong Zhao

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  1. ZiXuan Huang
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Correspondence to ZiXuan Huang.

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Huang, Z., Niu, B., Zhao, N. et al. State Observer-Based Composite Adaptive Fault-Tolerant Fuzzy Control for Uncertain Nonlinear Systems with Quantized Inputs. Int. J. Fuzzy Syst. 26, 1664–1680 (2024). https://doi.org/10.1007/s40815-024-01696-1

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