Earticle

초록

영어

An adaptive backstepping controller is proposed for a class of nonlinear systems with hysteresis and unknown control direction. As the unknown gain sign is combined with multi-valued non-smooth hysteresis together, it is more challengeable to mitigate hysteresis effects and meanwhile guarantee stability of the dynamic systems. In this paper, Bouc-Wen model is adopted to describe the hysteresis. Then RBF neural networks are applied to approximate the unknown functions. The unknown control direction is solved by Nussbaum function. The adaptive backstepping controller is developed using prescribed performance function to confine the error to a predefined residual set. It is proved that all the closed-loop signals are bounded and the tracking error converges to an arbitrarily small field. Finally, the simulation result shows the feasibility of the control scheme.

목차

Abstract
 1. Introduction
 2. System Description
 3. Controller Design
  3.1. Nussbaum Function
  3.2. Error Transformation
  3.3. Adaptive Neural Network Control
 4. Simulation Results
 5. Conclusion
 References

키워드

저자

• Xinlong Zhao [ College of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou Zhejiang, China ]
• Jiali Wang [ College of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou Zhejiang, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605