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| FUZZY SUPERVISION OF ROBOTIC EXCAVATOR RESEARCH ON NEURAL NETWORK CONTROLLERS |
| GONG Xiangdong, WANG Jianzhi, FENG Pien, GAO Yu |
| The State Key Laboratory for Fluid Power Transmission and Control in Zhejiang University 310027 |
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Abstract A method of rule-based self-learning neural-network controller applied to the robotic excavator is presented. According to the real-time control result, the controller takes advantage of the method of multiple-steps learning and fuzzy supervision to correct the teacher signals of neural-network, therefore, the control algorithm becomes simple, the reality of calculating is improved, and the learning speed is increased. This method is tested and verified by experiments.
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Received: 09 November 1995
Published: 15 September 1996
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