Neural Adaptive Compensation Control for a Class of MIMO Uncertain Nonlinear Systems with Actuator Failures

Abstract

A neural adaptive compensation control scheme for a class of multi-input multi-ouput (MIMO) uncertain nonlinear systems with actuator failures is proposed based on prescribed performance bound (PPB) transient performance which characterizes the convergence rate and maximum overshoot of the tracking error. RBF neural networks are used to approximate the… (More)
DOI: 10.1007/s00034-013-9716-y

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