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Optimized Fuzzy Enhanced Robust Control Design for a Stewart Parallel Robot

Author

Listed:
  • Mai The Vu

    (School of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea
    These authors contributed equally to this work.)

  • Khalid A. Alattas

    (Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah 23218, Saudi Arabia
    These authors contributed equally to this work.)

  • Yassine Bouteraa

    (Department of Computer Engineering, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
    Control and Energy Management Laboratory (CEM Lab.), Ecole Nationale d Ingenieurs de Sfax (ENIS), Institut Superieur de Biotechnologie de Sfax (ISBS), University of Sfax, Sfax 3038, Tunisia)

  • Reza Rahmani

    (Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu 64002, Yunlin, Taiwan)

  • Afef Fekih

    (Department of Electrical and Computer Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

  • Saleh Mobayen

    (Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu 64002, Yunlin, Taiwan)

  • Wudhichai Assawinchaichote

    (Department of Electronic and Telecommunication Engineering, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand)

Abstract

The remarkable properties of sliding mode control (SMC)—such as robustness, accuracy, and ease of implementation—have contributed to its wide adoption by the control community. To accurately compensate for parametric uncertainties, the switching part of the SMC controller should have gains that are sufficiently large to deal with uncertainties, but sufficiently small to minimize the chattering phenomena. Hence, proper adjustment of the SMC gains is crucial to ensure accurate and robust performance whist minimizing chattering. This paper proposes the design and implementation of an optimal fuzzy enhanced sliding mode control approach for a Stewart parallel robot platform. A systematic approach of designing the table of rules of the fuzzy system so as to provide the required coefficients of the sliding mode controller is proposed. The aim is to attain optimum performance and minimum control effort, thus eliminating the need for computationally expensive expert systems and yielding control outputs below the actuator saturation ranges. The proposed approach was validated using a six degrees-of-freedom Stewart platform subject to external disturbances. Its performance was compared to that of a standard SMC approach. The obtained results and comparative study showed that the proposed control algorithm not only reduces chattering, but also responds effectively to the realistic demands of control energy, while preventing actuator saturation.

Suggested Citation

  • Mai The Vu & Khalid A. Alattas & Yassine Bouteraa & Reza Rahmani & Afef Fekih & Saleh Mobayen & Wudhichai Assawinchaichote, 2022. "Optimized Fuzzy Enhanced Robust Control Design for a Stewart Parallel Robot," Mathematics, MDPI, vol. 10(11), pages 1-36, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1917-:d:831041
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    References listed on IDEAS

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    1. Mojtaba Ahmadieh Khanesar & David Branson, 2022. "Robust Sliding Mode Fuzzy Control of Industrial Robots Using an Extended Kalman Filter Inverse Kinematic Solver," Energies, MDPI, vol. 15(5), pages 1-17, March.
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    Cited by:

    1. Yassine Bouteraa & Khalid A. Alattas & Obaid Alshammari & Sondess Ben Aoun & Mohamed Amin Regaieg & Saleh Mobayen, 2022. "Interval Fuzzy Type-2 Sliding Mode Control Design of Six-DOF Robotic Manipulator," Mathematics, MDPI, vol. 10(24), pages 1-52, December.
    2. Ayman A. Aly & Mai The Vu & Fayez F. M. El-Sousy & Ahmed Alotaibi & Ghassan Mousa & Dac-Nhuong Le & Saleh Mobayen, 2022. "Fuzzy-Based Fixed-Time Nonsingular Tracker of Exoskeleton Robots for Disabilities Using Sliding Mode State Observer," Mathematics, MDPI, vol. 10(17), pages 1-19, September.
    3. Mai-The Vu & Kuo-Hsien Hsia & Fayez F. M. El-Sousy & Thaned Rojsiraphisal & Reza Rahmani & Saleh Mobayen, 2022. "Adaptive Fuzzy Control of a Cable-Driven Parallel Robot," Mathematics, MDPI, vol. 10(20), pages 1-16, October.

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