Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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The Adaptive Backstepping Controller of RBF Neural Network Which is Designed on the Basis of the Error

오차를 기반으로한 RBF 신경회로망 적응 백스테핑 제어기 설계

  • Kim, Hyun Woo (Graduate School, Department of Automotive Engineering, Hanyang University) ;
  • Yoon, Yook Hyun (Graduate School, Department of Automotive Engineering, Hanyang University) ;
  • Jeong, Jin Han (Graduate School, Department of Automotive Engineering, Hanyang University) ;
  • Park, Jahng Hyon (Graduate School, Department of Automotive Engineering, Hanyang University)
  • 김현우 (한양대학교 대학원 미래자동차공학과) ;
  • 윤육현 (한양대학교 대학원 미래자동차공학과) ;
  • 정진한 (한양대학교 대학원 미래자동차공학과) ;
  • 박장현 (한양대학교 대학원 미래자동차공학과)
  • Received : 2016.07.25
  • Accepted : 2016.10.12
  • Published : 2017.02.01
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Abstract

2-Axis Pan and Tilt Motion Platform, a complex multivariate non-linear system, may incur any disturbance, thus requiring system controller with robustness against various disturbances. In this study, we designed an adaptive backstepping compensated controller by estimating the disturbance and error using the Radial Basis Function Neural Network (RBF NN). In this process, Uniformly Ultimately Bounded (UUB) was demonstrated via Lyapunov and stability was confirmed. By generating progressive disturbance to the irregular frequency and amplitude changes, it was verified for various environmental disturbances. In addition, by setting the RBF NN input vector to the minimum, the estimated disturbance compensation process was analyzed. Only two input vectors facilitated compensatory function of RBF NN via estimating the modeling and control error values as well as irregular disturbance; the application of the process resulted in improved backstepping controller performance that was confirmed through simulation.

Keywords

References

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