Nonlinear Fuzzy Model Predictive Control of the TCP-100 Parabolic Trough Plant

Abstract

Advanced control strategies can play an important role in improving the efficiency of solar plants. In particular, linear model predictive control strategies have been applied successfully when controlling solar trough plants. However, if the control algorithm uses a linear model associated only with one operating point, when the plant is working far from the design conditions, the performance of the controller may deteriorate. In this paper, a fuzzy model-based nonlinear model predictive controller is applied to the new TCP-100 solar facility. The control strategy uses a fuzzy model of the plant for predicting the future evolution of the outlet temperature. This approach reduces the computational time of the nonlinear model predictive control strategy and allows to solve it much faster than using the full nonlinear model.