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Taylor Series-Based Fuzzy Model Predictive Control for Wheeled Robots

Author

Listed:
  • Libo Yang

    (School of Mechanical and Electrical Engineering, Guangdong University of Science and Technology, Dongguan 523083, Guangdong, China)

  • Mei Guo

    (School of Computer and Artificial Intelligence, Xiangnan University, Chenzhou 423000, Hunan, China
    Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems, Chenzhou 423000, Hunan, China)

  • Ardashir Mohammadzadeh

    (Multidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Amir Mosavi

    (Faculty of Civil Engineering, Technische Universität Dresden, 01067 Dresden, Germany
    John von Neumann Faculty of Informatics, Obuda University, 1034 Budapest, Hungary
    Institute of Information Engineering, Automation and Mathematics, Slovak University of Technology in Bratislava, 81237 Bratislava, Slovakia)

Abstract

In this paper, a new hybrid method for controlling a wheeled robot is introduced. Model predictive control (MPC) is the main controller and a fuzzy controller is used as a compensator. The wheeled robot is a nonlinear, multi-input–multi-output system that requires new and combined methods for precise control. In order to stabilize the system the appropriate control input is set, and at the same time, attention is paid to the reference signal tracking. In the simulation section, several different scenarios are applied and parameter uncertainties and their effects on the controller’s performance are evaluated. The simulation results show the success and efficiency of the proposed method.

Suggested Citation

  • Libo Yang & Mei Guo & Ardashir Mohammadzadeh & Amir Mosavi, 2022. "Taylor Series-Based Fuzzy Model Predictive Control for Wheeled Robots," Mathematics, MDPI, vol. 10(14), pages 1-13, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2498-:d:865464
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    References listed on IDEAS

    as
    1. Haifeng Huang & Mohammadamin Shirkhani & Jafar Tavoosi & Omar Mahmoud, 2022. "A New Intelligent Dynamic Control Method for a Class of Stochastic Nonlinear Systems," Mathematics, MDPI, vol. 10(9), pages 1-15, April.
    2. Hongwei Mo & Qirong Tang & Longlong Meng, 2013. "Behavior-Based Fuzzy Control for Mobile Robot Navigation," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-10, September.
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    Cited by:

    1. Xin Xu & Ahmed Shaker & Marwa S. Salem, 2022. "Automatic Control of a Mobile Manipulator Robot Based on Type-2 Fuzzy Sliding Mode Technique," Mathematics, MDPI, vol. 10(20), pages 1-18, October.

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