Design and implementation of fuzzy controllers for complex systems - case study: a water desalination plant

Two soft computing paradigms for automated learning control of complex systems are briefly de scribed. To illustrate the utility of the paradigms, they are applied to a desalination process and sim ulations are performed. The first paradigm in corporates Genetic Algorithms (GA) in a learn ing scheme to adapt parameters of the fuzzy controller to changing environmental conditions. The second paradigm concentrates on a methodology which uses a Neural Network (NN) to adapt a fuzzy logic controller. Simulation results of fuzzy controllers learned with the aid of these soft computing paradigms are presented.