Constrained Temperature Control of a Solar Furnace

• Published in: IEEE transactions on control systems technology Vol. 20; no. 5; pp. 1263 - 1274
• Main Authors: Beschi, M., Visioli, A., Berenguel, M., Yebra, L. J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.09.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptative systems; Apertures; Applied sciences; Computer science; control theory; systems; Constrained control; Constraints; Control system synthesis; Control theory. Systems; Devices using thermal energy; Dynamical systems; Dynamics; Energy; Energy. Thermal use of fuels; Exact sciences and technology; Feedforward control; Feedforward neural networks; Furnaces; Law; optimization; Phases; Process control; set-point regulation; solar furnace; Solar furnaces; Solar radiation; Strategy; Temperature control; Control program; Control synthesis; set-point regulation; Dynamical system; feedforward control; Adaptive control; Cantilever beam; Control constraint; Rotating system; Minimum time; Phase velocity; Maximum velocity; Solar furnace; optimization; Constrained control; Feedforward; State constraint; Set point; Saturation; Overshoot; Output signal; Experimental study; Ramp signal; Constrained optimization; Reference model; Temperature control; Rotating beam(mechanics)
• ISSN: 1063-6536; 1558-0865
• DOI: 10.1109/TCST.2011.2164795

A new constrained control strategy for a solar furnace is proposed in this paper with the goal of attaining a minimum-time transition between two values of the temperature subject to constraints on both the saturation and slew rate level of the process input. In the case of set-point step-shape signals, the strategy basically consists in implementing a (model-based) feedforward control law with maximum positive and negative velocity phases in order to obtain a minimum-time transition with no overshoot. In the case of ramp-shape set-point signals (addressing the output slew-rate constraint), the suitable feedforward control law is obtained by also inverting the dynamics of the system. Implementation issues are discussed. Simulation and real experimental results demonstrate the effectiveness of the methodology.