Fuzzy control technique based on genetic algorithms optimizing and its application

Aimed at a type of complex industrial production process with nonlinear dynamic properties, the Fuzzy Neural Network controller based on Genetic Algorithms was designed. The coding optimization method for the parameters of the stimulating functions of the network's hidden nodes is the concatenated, multi parameter, mapped, and fixed point coding method. Based on this method, we can get the optimized fuzzy controller online. The step response curve of practical oven temperature control is given. The experimental results show that optimization via the Fuzzy Neural Network controller based on Genetic Algorithms is robust and effective and will find wide industrial application scope.