P. Gil, J. Henriques, A. Cardoso, and A. Dourado (Portugal)
: Neural networks; Input space partitioning; Scheduling PID control; Solar power plants.
This work presents a hybrid scheme combining the potentialities of neural networks for approximation purposes with the well-know theory and widespread industrial application of PID techniques. The neural network is trained based on measured data from the plant providing a way of scheduling between a set of PID controllers, a priori tuned in different operating points by means of Takahashi rules. This neural network control strategy is in practice applied to the control of a distributed collector field of a solar power plant. Experimental results collected at Plataforma Solar de Almeria (Spain), show the effectiveness of the proposed approach.
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