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An Adaptive Fuzzy Terminal Sliding Mode Control Methodology for Uncertain Nonlinear Second-Order Systems

  • Anh Tuan Vo
  • Hee-Jun Kang
  • Tien Dung Le
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10954)

Abstract

This paper introduces a novel control strategy for uncertain nonlinear second-order systems. Our strategy proposes a novel adaptive fuzzy sliding mode controller, which based on a combination of a new non-singular fast terminal sliding variable and a continuous control algorithm. In this paper, our main contribution is to contain benefits of non-singular fast terminal sliding variables such as fast convergence and no singularity drawback along with strong robustness in the frame of perturbation and uncertainty. In the suggested controller, a continuous control law is added to refuse the drawbacks of sliding mode control about consideration on upper bound value of perturbations and uncertainties. Unfortunately, it is remarkable difficult for a real system to identify those upper bound limits in advance. It is reminded that to deal with above concern, a fuzzy logic control algorithm with adaptive updating law can be used to approximate switching control law. Thanks to this technique, the perturbations and uncertainties can be eliminated without chattering behavior in control input. Accordingly, the strong robustness and the stability of the suggested system is then secured with high accuracy performance. The robustness topic of the suggested system is also completely proven by Lyapunov approach. In our numerical simulation, performances comparison among the suggested control strategy, a sliding mode controller, and a non-singular terminal sliding mode controller are specifically performed. Our simulation result demonstrates the effectiveness, practicality of suggested control strategy for the joint position tracking control of a 3-DOF PUMA560 robot.

Keywords

Uncertain nonlinear second-order systems Non-singular fast terminal sliding mode Fuzzy logic system Adaptive control law 

Notes

Acknowledgement

This work was supported by the University of Ulsan, Ulsan, Korea.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Graduate School of Electrical EngineeringUniversity of UlsanUlsanSouth Korea
  2. 2.School of Electrical EngineeringUniversity of UlsanUlsanSouth Korea
  3. 3.The University of Danang - University of Science and TechnologyDanangVietnam

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