Adaptive neural model-based predictive control of a solar power plant
Proceedings of the 2002 International Joint Conference on Neural …, 2002•ieeexplore.ieee.org
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.
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.
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.
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