Neuroadaptive control of elastic-joint robots using robust performance enhancement

Abstract

A neuroadaptive control scheme for elastic-joint robots is proposed that uses a relatively small neural network. Stability is achieved through standard Lyapunov techniques. For added performance, robust modifications are made to both the control law and the weight update law to compensate for only approximate learning of the dynamics. The estimate of the… (More)
DOI: 10.1017/S0263574799002155

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