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

被引:3
|
作者
Gil, P [1 ]
Henriques, J [1 ]
Carvalho, P [1 ]
Duarte-Ramos, H [1 ]
Dourado, A [1 ]
机构
[1] Univ Coimbra, CISUC Informat Engn Dept, P-3030 Coimbra, Portugal
关键词
solar power plant; state-space neural networks; online training; constrained model-based predictive control; dual unscented Kalman filter;
D O I
10.1109/IJCNN.2002.1007465
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes the application of a non-linear 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 non-linear modelling capabilities of non-linear 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.
引用
收藏
页码:2098 / 2103
页数:2
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