摘要
本文提出了用人工神经网络近似机械手的逆动力学模型,实现基于模型的非线性控制方案,并以实际的两臂液压机械手为对象给出了仿真结果,整个方案的实现不需要任何关于系统模型的知识.仿真结果表明所研究的位置控制系统具有良好的跟踪性能,并且展示了人工神经网络解决非线性系统辨识和控制问题的潜力.
Based on an artificial neural network inverse dynamic model of robot manipulators,a nonlinear model-based control scheme is presented in this paper.The implementation of the whole scheme assumes no anyknowledge of the system.The simulation tests for the two-link hydraulic robot manipulators indicate that theposition control system under consideration has acceptable good tracking performance,and demostrate thatartificial neural networks have potential of solying identification and control problems of nonlinear systems.
出处
《机器人》
EI
CSCD
北大核心
1993年第5期33-38,59,共7页
Robot
关键词
人工神经网络
逆动力学模型
位置控制
液压机械手
非线性
inverse dynamic model
artificial neural network
position control
hydraulic robot manipulators
nonlinear system
