I.S. Baruch and C.R. Mariaca G. (Mexico)
Adaptive control, integral terms, systems identification and state estimation, recurrent neural networks, discrete time-delay system, and simple effect evaporator.
A direct adaptive neural control scheme with single and double I-term is proposed to be applied for multivariable plant. The control scheme contains two Recurrent Trainable Neural Network (RTNN) models. The first RTNN is a plants parameter identifier and state estimator. The second RTNN is a feedback - feedforward controller with I-terms. The good performance of the adaptive neural control with I-terms is confirmed by closed-loop systems analysis, and by simulation results, obtained with simple effect evaporator multivariable plant, corrupted by noise and affected by small unknown input time delay.
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