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Adaptive Sliding Mode Control of Robot Manipulators with System Failures

Author

Listed:
  • Rui Li

    (School of Computer Engineering, Zhongshan Institute, University of Electronic Science and Technology, Zhongshan 528402, China
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Liang Yang

    (School of Computer Engineering, Zhongshan Institute, University of Electronic Science and Technology, Zhongshan 528402, China
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Yong Chen

    (School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Guanyu Lai

    (School of Automation, Guangdong University of Technology, Guangzhou 510006, China)

Abstract

This paper presents a novel adaptive sliding mode controller for a class of robot manipulators with unknown disturbances and system failures, which can well achieve the asymptotic tracking, and avoid some possible singularity problems. A new virtual controller is designed such that the chosen Lyapunov function can be transformed into a non-Lipschitz function, based on which, the system states can arrive at the specified sliding surface within a finite time regardless of the existence of system failures/faults. By fusing an integral fast terminal nonsingular SMC and a robust adaptive technique, the tracking error can be steered into a preset range in a set time and some possible singularity problems are avoided elegantly. With our proposed scheme, the loss coefficient is well estimated, and the stability of the system can be guaranteed even in the presence of the total loss of actuator outputs. The experiment and simulation results are presented to illustrate the effectiveness of the proposed control scheme.

Suggested Citation

  • Rui Li & Liang Yang & Yong Chen & Guanyu Lai, 2022. "Adaptive Sliding Mode Control of Robot Manipulators with System Failures," Mathematics, MDPI, vol. 10(3), pages 1-15, January.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:3:p:339-:d:731258
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    Citations

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    Cited by:

    1. Nguyen Xuan-Mung & Mehdi Golestani, 2022. "Smooth, Singularity-Free, Finite-Time Tracking Control for Euler–Lagrange Systems," Mathematics, MDPI, vol. 10(20), pages 1-18, October.
    2. Mohammad Hosein Sabzalian & Khalid A. Alattas & Fayez F. M. El-Sousy & Ardashir Mohammadzadeh & Saleh Mobayen & Mai The Vu & Mauricio Aredes, 2022. "A Neural Controller for Induction Motors: Fractional-Order Stability Analysis and Online Learning Algorithm," Mathematics, MDPI, vol. 10(6), pages 1-17, March.

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