Sliding Mode Control with RLSN Predictor-Based Perturbation Estimation

RLSN 예측기 기반 섭동 추정기를 갖는 슬라이딩 모드 제어

  • 남윤주 (부산대학교 지능기계공학과) ;
  • 이육형 (부산대학교 기계기술연구소) ;
  • 박명관 (부산대학교 기계공학부 및 기계기술연구소)
  • Published : 2006.08.01


This paper presents the sliding mode control with the perturbation estimator for a nonlinear control system in the presence of perturbations including external disturbances, unpredictable parameter variations, ana unstructured dynamics. The proposed perturbation estimator is based on the Recursive Linear Smoothed Newton predictive algorithm so that it is effective to attenuate an undesired noise in high frequency band and to predict the present perturbation signal from the previous ones. Compared to conventional sliding mode control (SMC) and sliding mode control with perturbation estimation (SMCPE) introduced by Elmali and Olgac, the control algorithm proposed in this study can offer better tracking control performances and more feasible estimation characteristics. The effectiveness and superiority of the proposed control strategy are demonstrated by a series of simulations on the position tracking control of a simple two-link robot manipulator subject to velocity feedback signals including white noises.


Perturbation Estimation;Recursive Linear Smoothed Newton Predictor;Robust Control;Sliding Mode Control


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