Direct Adaptive Neural Control Scheme with Integral-Plus-State Action

I.S. Baruch, A. del Carmen Martinez Q., and R. Garrido (Mexico)


Recurrent Neural Networks, Backpropagation Learning,Systems Identification, State Estimation, AdaptiveControl, Integral Plus State Action.


A direct adaptive neural control scheme with single and double Integral-Plus-State (IPS) action, is proposed. The control scheme contain two Recurrent Trainable Neural Network (RTNN) models, which are: a plants parameter identificator and state estimator, and an IPS feedback/feedforward controller. The good performance of the adaptive IPS control scheme is confirmed by closed-loop systems analysis, and by simulation results, obtained with MIMO plant, corrupted by noise.

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