Title :
Adaptive neural model-based predictive control of a solar power plant
Author :
Gil, P. ; Henriques, J. ; Carvalho, Paulo ; Duarte-Ramos, H. ; Dourado, A.
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper describes the application of a nonlinear adaptive constrained model-based predictive control scheme to the distributed collector field of a solar power plant at the Plataforma Solar de Almeria (Spain). This methodology exploits the intrinsic nonlinear modelling capabilities of nonlinear state-space neural networks and their online training by means of an unscented Kalman filter. Tests on the ACUREX field illustrate the great engineering potential of the proposed control strategy
Keywords :
Kalman filters; adaptive control; discrete time systems; learning (artificial intelligence); neurocontrollers; nonlinear systems; predictive control; real-time systems; solar power stations; state estimation; Kalman filter; Plataforma Solar de Almeria; adaptive control; constrained model-based control; discrete-time system; neurocontrol; nonlinear system; online training; predictive control; solar power plant; state-space neural networks; Adaptive control; Fluid flow control; Neural networks; Power engineering and energy; Power generation; Predictive control; Predictive models; Programmable control; Solar energy; Water heating;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007465
