Direct Adaptive Neural Control with Integral-Plus-State Action
نویسندگان
چکیده
The paper applied a Recurrent Neural Network (RNN) model in two Integral-Plus-State (IPS) schemes of real-time adaptive neural control. The proposed control modify and extend a previously published direct adaptive neural control scheme with one or two I-control terms, so to obtain a neural, IPS adaptive, offset compensational and trajectory tracking control. The control scheme contains only two RNN models (systems identificator and IPS feedback controller) and not need a third feedforward RNN control model. The good performance of the adaptive neural IPS control is confirmed by comparative simulation results, obtained using a nonlinear multi-input multi-output plant, corrupted by noise. The results exhibits good convergence and noise resistance which not depend on the magnitude of the offset.
منابع مشابه
Adaptive Neural Control with Integral-Plus-State Action
Abstract: An indirect adaptive neural control with Integral-Plus-State (IPS) action, is proposed. The control scheme contain one identification and state estimation Recurrent Trainable Neural Network. The identified plant parameters and the estimated state vector are used to compute an adaptive IPS control. Two control schemes are proposed, containing one or two integrals in the control law. Th...
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