Hybrid control and evolutionary decision support within a sustainable environment

Due to the increasing global demand for energy, and the potential dangers of relying too heavily on our fossil fuel reserves, more and more research is being directed towards alternative, and preferably reusable or sustainable forms of energy supply. Many of these real world systems have operating regions or regimes that exhibit varying degrees of non-linearity. An example of this are the significant variations in the dynamic characteristics of a distributed collector field within a solar power plant. Here a control scheme employs a fuzzy PI controller, with feedforward, for the highly nonlinear part of the operating regime and gain scheduled controller for 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 with an enhanced decision support system, is used, to design the parameters of the fuzzy controller.