Gain-scheduled control of a solar power plant using a hierarchical MOGA-tuned fuzzy PI-controller

In order to regulate the significant variations in the dynamic characteristics of a distributed collector field in a solar power plant, various control techniques including feedforward control, gain scheduling and fuzzy control have been considered in the past. This paper develops some of these previous approaches by considering the operating conditions of the plant and the desired controlled responses. The result is a control scheme that employs a fuzzy PI controller, with feedforward, for the highly nonlinear part of the operating regime and gain scheduled control over the more linear part of the operating envelope. In order to satisfy performance characteristics for the plant at different points in the operating regime, a multiobjective genetic algorithm is used to design the parameters of the fuzzy controller. To reduce the size of the search space and the resulting fuzzy controller, a hierarchical encoding is employed with the multiobjective genetic algorithm. The resulting controller is shown to both satisfy the desired performance criteria and have a reduced number of terms compared with a conventional design approach