DateThe final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline.iii can preserve product quality and maintain stable product compositions, resulting in a more efficient and cost-effective operation, which can ultimately lead to scale-up and commercialization of solar thermochemical technologies.
ABSTRACTIn this work, we propose a model predictive control (MPC) system for a solar-thermal reactor for the steam-gasification of biomass. The proposed controller aims at rejecting the disturbances in solar irradiation caused by the presence of clouds. A first-principles dynamic model of the process was developed. The model was used to study the dynamic responses of the process variables and to identify a linear time-invariant model used in the MPC algorithm.To provide an estimation of the disturbances for the control algorithm, a one-minute-ahead direct normal irradiance (DNI) predictor was developed. The proposed predictor utilizes information obtained through the analysis of sky images, in combination with current atmospheric measurements, to produce the DNI forecast.In the end, a robust controller was designed capable of rejecting disturbances within the operating region. Extensive simulation experiments showed that the controller outperforms a iv finely-tuned multi-loop feedback control strategy. The results obtained suggest that our controller is suitable for practical implementation.v