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Adaptive Control for Uncertain Model of Omni-directional Mobile Robot Based on Radial Basis Function Neural Network

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Abstract

The paper proposes the method to deal with control problems of unmodeled components of the four-wheeled Omni-directional mobile robot. It is commonly challenging to design a model-based control scheme to achieve smooth movement in the tracking process due to the unknown elements in the mathematical model of the robot or external disturbances. Our main contribution focuses on designing an adaptive controller based on neural networks with online weight updating laws and Fuzzy logic to guarantee the high accuracy of the robot’s movement when the unknown factors adversely affect the robot control. At the initial step, a Dynamic Surface Control plays a role as a core of the controller for the robot system. Then, with the ability to estimate the appropriate value for uncertain nonlinear parts, a Radial Basis Function Neural Network is designed. Finally, a Fuzzy law is to utilize control parameters in each period to increase the adaptive behavior of the system. The stability and convergence of the system are proven by the Lyapunov’s stability theory. The simulation results illustrate the validity and the efficiency of the proposed control algorithm when the system is lack of robot model’s information.

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Author information

Authors and Affiliations

  1. Hanoi University of Industry, 298 Cau Dien, Bac Tu Liem District, Hanoi, Vietnam

    Duyen Ha Thi Kim

  2. Institute of Physics, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, Cau Giay District, Hanoi, Vietnam

    Tien Ngo Manh, Cuong Nguyen Manh, Dung Pham Tien & Manh Tran Van

  3. Sungkyunkwan University, Suwon, Korea

    Nhan Duc Nguyen

  4. Hanoi University of Science and Technology, Dai Co Viet, Hanoi, Vietnam

    Minh Phan Xuan

Authors
  1. Duyen Ha Thi Kim
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Corresponding author

Correspondence to Tien Ngo Manh.

Additional information

Recommended by Associate Editor Sung Jin Yoo under the direction of Editor Euntai Kim.

This research was funded by Project “Research, Design And Manufacturing Smart Human-Form IVASTBot Robot Applied In Communication And Serving Human” coded VAST01.01/20–21 implemented by the Institute of Physics, Vietnam Academy of Science and Technology.

Duyen Ha Thi Kim graduated with Engineering Degree in automatic control at Hanoi University of Science and Technology (HUST) from 1996–2001. She received her Master’s Degree at Le Quy Don Technical University in 2007. Now, she works at the School of Electronic — Hanoi University of Industry. Her main research areas include process control, PLC controller and industrial communication network, adaptive control, fuzzy logic, and neural network control.

Tien Ngo Manh graduated Engineering Degree in automatic control at Hanoi University of Science and Technology (HUST) from 1996–2001. He received his Doctor’s Degree in electrical engineering at HUST in 2014. Now, he works at the Institute of Physics, Vietnam Academy of Science and Technology. His main research areas include process control, adaptive control, fuzzy logic and neural network control, automatic robot control, electro-optical system, image processing.

Cuong Nguyen Manh is a senior student major in electrical — automatic control at Hanoi University of Science and Technology (HUST). Now, he is working at Institute of Physics, Vietnam Academy of Science and Technology. His main research area include adaptive control, fuzzy logic and neural network control, and robot operating system programing for robotics.

Nhan Duc Nguyen received his E.E. degree in automatic control from the Hanoi University of Science and Technology, Hanoi, Vietnam, in 2015, and an M.S. degree in electrical engineering from Kookmin University, Seoul, Korea in 2018. He is currently pursuing a Ph.D degree in biomedical engineering with Sungkyunkwan University, Korea. His research interests include robotics, pattern recognition, machine learning, and deep learning.

Dung Pham Tien is a senior student major in electrical — automatic control at Hanoi University of Science and Technology (HUST). Now, He is working at the Institute of Physics, Vietnam Academy of Science and Technology. His main research areas include adaptive control, fuzzy logic and neural network control, and robot operating system programing for robotics.

Manh Tran Van is a senior student major in electrical — automatic control at Hanoi University of Science and Technology (HUST). Now, he is working at the Institute of Physics, Vietnam Academy of Science and Technology. His main research areas include adaptive control, fuzzy logic and neural network control, and robot operating system programing for robotics.

Minh Phan Xuan received her Master of Engineering Degree (1976) and Doctorate Degree (1989), major in automatic control at Ilmenau University of Technology, Ilmenau, Germany. She is a professor at the School of Electrical Department — Automatic Control at Hanoi University of Science and Technology. Her main research areas include optimize control, adaptive control, fuzzy logic and neural network control, and process control.

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Kim, D.H.T., Manh, T.N., Manh, C.N. et al. Adaptive Control for Uncertain Model of Omni-directional Mobile Robot Based on Radial Basis Function Neural Network. Int. J. Control Autom. Syst. 19, 1715–1727 (2021). https://doi.org/10.1007/s12555-019-1004-6

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  • DOI: https://doi.org/10.1007/s12555-019-1004-6

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