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Adaptive sliding mode control with information concentration estimator for a robot arm

Author

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  • Xiaofei Zhang
  • Hongbin Ma
  • Man Luo
  • Xiaomeng Liu

Abstract

There are nonlinear disturbances in actual systems, and all kinds of nonlinear disturbances may make the performances of actual systems become worse, besides, sometimes it is difficult to obtain a simplified model of the actual system owing to complex production technologies and processes. The existence of both two kinds of uncertainties makes it difficult to directly apply traditional recursive identification methods based on parametric systems. In this paper, first, an improved information concentration (IC) estimator is introduced for estimating unknown parameters of parametric uncertainty part by using historical data, and an adaptive sliding mode controller based on the proposed IC estimator is investigated for the speed control system of a robot arm. Second, the stability of adaptive sliding mode control based on the proposed IC estimator for the speed control system of a robot arm is analysed. Finally, two simulation examples are carried out. The experimental results indicate that the proposed IC estimator is effective in estimating unknown parameters.

Suggested Citation

  • Xiaofei Zhang & Hongbin Ma & Man Luo & Xiaomeng Liu, 2020. "Adaptive sliding mode control with information concentration estimator for a robot arm," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(2), pages 217-228, January.
    • Handle: RePEc:taf:tsysxx:v:51:y:2020:i:2:p:217-228
    DOI: 10.1080/00207721.2019.1691752
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    Cited by:

    1. Jiacheng Wang & Yunmei Fang & Juntao Fei, 2023. "Adaptive Super-Twisting Sliding Mode Control of Active Power Filter Using Interval Type-2-Fuzzy Neural Networks," Mathematics, MDPI, vol. 11(12), pages 1-20, June.
    2. Yin, Xiang & She, Jinhua & Wu, Min & Sato, Daiki & Ohnishi, Kouhei, 2022. "Disturbance rejection using SMC-based-equivalent-input-disturbance approach," Applied Mathematics and Computation, Elsevier, vol. 418(C).

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