LINGUISTIC SELF-ORGANIZING PROCESS CONTROLLER USING GENETIC ALGORITHM

A linguistic self-organizing controller using genetic algorithm is presented, whose control policy is able to generate, develop and improve. The scaling factors can be chosen automatically.Optimizing the scaling factors by genetic algorithm instead of trial or experimental method which is often used in conventional linguistic self-organizing controller eliminates the drawback of an exhausive search of the GE*GC*GU space by human operator, and also produces the better system response and a set of better control rules. A number of simulations on linear dynamic systems as well as non-linear systems such as second order process with a random disturbance, third order process with time lags and the cart-pole balancing problem etc. are described in this paper, which shows that the controller has strong adaptive properties and gives better performance than that of the conventional linguistic self-organizing controller.

LINGUISTIC SELF-ORGANIZING PROCESS CONTROLLER USING GENETIC ALGORITHM

A linguistic self-organizing controller using genetic algorithm is presented, whose control policy is able to generate, develop and improve. The scaling factors can be chosen automatically. Optimizing the scaling factors by genetic algorithm instead of trial or experimental method which is often used in conventional linguistic self-organizing controller eliminates the drawback of an exhausive search of the GE * GC* GU space by human operator, and also produces the better system response and a set of better control rules. A number of simulations on linear dynamic systems as well as non-linear systems such as second order process with a random disturbance, third order process with time lags and the cart-pole balancing problem etc. are described in this paper, which shows that the controller has strong adaptive properties and gives better performance than that of the conventional linguistic self-organizing controller.