Neural Output Regulation for a Solar Power Plant

Abstract

Abstract:In this paper the modelling capabilities of a recurrent neural network and the effectiveness and stability of the output regulation control theory are combined. The control structure consists in a neural based indirect adaptive control scheme, being the main goal to provide a viable practical control strategy suitable for real-time implementations. This control scheme was applied to the distributed solar collector field at Plataforma Solar de Almería, Spain. Experimental results obtained at the solar power plant are presented showing the effectiveness of the proposed approach.