Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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A Novel Neural Network Compensation Technique for PD-Like Fuzzy Controlled Robot Manipulators

PD 기반의 퍼지제어기로 제어된 로봇의 새로운 신경회로망 보상 제어 기술

  • 송덕희 (충남대학교 메카트로닉스공학과) ;
  • 정슬 (충남대학교 메카트로닉스공학과)
  • Published : 2005.06.01
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Abstract

In this paper, a novel neural network compensation technique for PD like fuzzy controlled robot manipulators is presented. A standard PD-like fuzzy controller is designed and used as a main controller for controlling robot manipulators. A neural network controller is added to the reference trajectories to modify input error space so that the system is robust to any change in system parameter variations. It forms a neural-fuzzy control structure and used to compensate for nonlinear effects. The ultimate goal is same as that of the neuro-fuzzy control structure, but this proposed technique modifies the input error not the fuzzy rules. The proposed scheme is tested to control the position of the 3 degrees-of-freedom rotary robot manipulator. Performances are compared with that of other neural network control structure known as the feedback error learning structure that compensates at the control input level.

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References

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