지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2008.10
- 수록면
- 2,569 - 2,574 (6page)
이용수
초록· 키워드
오류제보하기
This paper presents an application of an adaptive neuro-fuzzy controller for compensating friction and disturbance effects on robot manipulators. The frictions and disturbances are important parts of the dynamic system of a robot manipulator. However, they are highly nonlinear and not easily modeled. Feedback linearization control combined with PD type fuzzy control and adaptive neural network control are proposed to control robot manipulators with unmodeled frictions. The feedback linearization control is designed to control the trajectory of the robot manipulator while the PD type fuzzy control is added as a parallel controller to control frictions and disturbances. This fuzzy control ensures that good tracking control is maintained even if some modeling error, disturbance, noises exist. The neural network can also be trained with experimental data for the frictions and disturbances. Simulations show that the joint positions are well controlled under wide variation of operation conditions and existences of uncertainties.
목차
Abstract
1. INTRODUCTION
2. FEEDBACK LINEARIZATION CONTROL
3. FEEDBACK LINEARIZATION COMBINED WITH A PD TYPE FUZZY CONTROL
4. ADAPTIVE NEURAL NETWORK CONTROLLER
6. CONCLUSION
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2014-569-000977530