LEARNING
Robust force/motion control of constrained robots using neural network
Chiman Kwan, Aydın Yeşildirek, Frank L. Lewis
- 发表年份
- 1999
- 引用次数
- 23
摘要
A robust neural network (NN) controller is proposed for the simultaneous force/motion control of constrained rigid robots. The NN weights here are tuned on-line, with no off-line learning phase required. Most importantly, we can guarantee the boundedness of constraint force errors, joint position tracking errors, and NN weights. When compared with adaptive controllers, we do not require linearity in the unknown parameters, and the tedious computation of the regression matrix. Novel passivity properties of the NN controller are stated and proven. ©1999 John Wiley & Sons, Inc.
关键词
Control theory (sociology)Artificial neural networkConstraint (computer-aided design)Controller (irrigation)RobotComputer sciencePosition (finance)PassivityComputationMotion control
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