Scheduling of PID controllers by means of a neural network with application to a solar power plant

This paper concerns the application of a neural network control strategy to the distributed collector field of a solar power plant 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 timed in different operating points by means of Takahashi rules. The present work consists in a hybrid scheme combining the potentialities of neural networks for approximation purposes with the well-know theory and widespread industrial application of BID techniques. Experimental results collected at Plataforma Solar de Almeria (Spain), show the effectiveness of the proposed approach.