Supervision and c-Means clustering of PID controllers for a solar power plant

Abstract A hierarchical control strategy consisting on a supervisory switching of PID controllers, simplified using the c-Means clustering technique, is developed and applied to the distributed collector field of a solar power plant. The main characteristic of this solar plant is that the primary energy source, the solar radiation, cannot be manipulated. It varies throughout the day, causing changes in plant dynamics conducting to distinct several operating points. To guarantee good performances in all operating points, a local PID controller is tuned to each operating point and a supervisory strategy is proposed and applied to switch among these controllers accordingly to the actual measured conditions. Each PID controller has been tuned off-line, by the combination of a dynamic recurrent non-linear neural network model with a pole placement control design. To reduce the number of local controllers, to be selected by the supervisor, a c-Means clustering technique was used. Simulation and experimental results, obtained at Plataforma Solar de Almeria, Spain, are presented showing the effectiveness of the proposed approach.