Abstract
This paper proposes a novel model-free adaptive sliding mode controller for nonlinear systems with uncertainties. The use of model-free control philosophy avoids the impact of inaccurate modeling on the system. The control accuracy and robustness of the system are improved by adopting the sliding mode algorithm. The adaptive gain and saturation function are used to reduce system chattering. Further, to address the problem of parameter changes and external strong disturbance during system operation, a new extended state observer (ESO) is proposed, and the observed state errors is ensured to asymptotically converge to zero. Finally, simulation experiment results are verified the effectiveness of the proposed control strategy.
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This research work is supported in part by the National Natural Science Foundation under Grant 62273189 and the Shandong Province Natural Science Foundation under Grant ZR2021MF005.
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Meng, X., Yu, H., Zhang, J., Zhang, K., Yang, Q. (2023). Model-Free Adaptive Sliding Mode Control for Nonlinear Systems with Uncertainties. In: Deng, Z. (eds) Proceedings of 2023 Chinese Intelligent Automation Conference. CIAC 2023. Lecture Notes in Electrical Engineering, vol 1082. Springer, Singapore. https://doi.org/10.1007/978-981-99-6187-0_55
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DOI: https://doi.org/10.1007/978-981-99-6187-0_55
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