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
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.8 No.3
- 발행연도
- 2008.9
- 수록면
- 185 - 191 (7page)
이용수
초록· 키워드
오류제보하기
In this paper, experimental studies of a neural network (NN) control technique for non-model based position control of the x-y table robot are presented. Decentralized neural networks are used to control each axis of the x-y table robot separately. For an each neural network compensator, an inverse control technique is used. The neural network control technique called the reference compensation technique (RCT) is conceptually different from the existing neural controllers in that the NN controller compensates for uncertainties in the dynamical system by modifying desired trajectories. The back-propagation learning algorithm is developed in a real time DSP board for on-line learning. Practical real time position control experiments are conducted on the x-y table robot. Experimental results of using neural networks show more excellent position tracking than that of when PD controllers are used only.
목차
Abstract
1. Introduction
2. PD Control of x-y Table Robot
3. Neural Network Compensation Technique
4. Learning Algorithms
5. Experimental Studies
6. Conclusion
References
참고문헌 (16)
참고문헌 신청
W. T. Miller , 1991 , Neural networks for Control , The MIT Press
K. Narendra , 1993 , Control of nonlinear dynamical systems using neural networks: controllability and stabilization , IEEE Trans. on Neural Networks 4 (2) : 192 ~ 206
S. Jung , 1995 , A new neural network control technique for robot manipulators , Robotica 13 : 477 ~ 484
H. Gomi , 1990 , Learning control for a closed loop system using feedback error learning , Proc. of the IEEE International Conf. on Decision and Control 3289 (3294) : 3289 ~ 3294
S. Omatu , 1998 , Neuro-control for single-input multi-output systems , IEEE Conf. on Knowledge Based Intelligent Electronics Systems 202 (205) : 202 ~ 205
K. Narendra , 1993 , Control of nonlinear dynamical systems using neural networks: controllability and stabilization , IEEE Trans. on Neural Networks 4 (2) : 192 ~ 206
S. Jung , 1995 , A new neural network control technique for robot manipulators , Robotica 13 : 477 ~ 484
H. Gomi , 1990 , Learning control for a closed loop system using feedback error learning , Proc. of the IEEE International Conf. on Decision and Control 3289 (3294) : 3289 ~ 3294
S. Omatu , 1998 , Neuro-control for single-input multi-output systems , IEEE Conf. on Knowledge Based Intelligent Electronics Systems 202 (205) : 202 ~ 205
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