Linear quadratic tracking-feedforward controller with robust stability for solar furnaces

Solar energy represents a versatile renewable source that can be used in materials resistance experiments through solar furnaces. This article examines the application of optimal controllers based on linear quadratic tracking with feedforward control action (LQTFF) to control solar furnaces used in material thermal stress tests. The proposed LQT-FF controller is based on previous studies that offer ff er an analytical solution based on a linear model of the solar furnace, thereby reducing the computational cost of the optimal control algorithm. The main contribution of this work lies in the incremental formulation of this model, incorporating an artificial integrator to the original states. Additionally, robust stability analysis is used to tune the LQT-FF, considering the closed-loop state estimator. The proper functioning of the proposed controller has been verified on a nonlinear model of the SF60 solar furnace at the Plataforma Solar de Almer & imath;<acute accent>a. The obtained results represent a significant advance in existing optimal controllers in the literature, as the LQT-FF controller results in an optimal control law with disturbance rejection formulated through an incremental form of inputs, which eliminates reference tracking error with stable tuning for the entire operating range of the plant. On the other hand, this control law can be efficiently ffi ciently implemented with lower computational effort, ff ort, which is crucial for its implementation.