Adaptive neural model-based predictive control of a solar power plant

Author

Gil, P. ; Henriques, J. ; Carvalho, Paulo ; Duarte-Ramos, H. ; Dourado, A.

Volume

3

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

2098

Lastpage

2103

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on

Conference_Location

Honolulu, HI

ISSN

1098-7576

Print_ISBN

0-7803-7278-6

Type

conf

DOI

10.1109/IJCNN.2002.1007465

Filename

1007465