Robust force/motion control of constrained robots using neural network

Abstract

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.