Theory Of Genetic Algorithm And Its Application In System Identification

Genetic algorithm is a searching algorithm that simulates biology evolvement in nature.Because of its briefness,strong robustness,especiallyit need not expert domain knowledge but fitness function as the value guidesearching process, its applications are very abroad.Based on variousMany systems in modern control project are shown as nonlinear, time-variantand uncertain. To achieve effective control, we should use model identification to obtain the approximate model to the object. Genetic algorithm is a kind of search algorithms that can be used in model identification and optimality calculation in complex system.Syetem identification problem can conclude system configuration identification and parameter identification.This thesis use genetic algorithm successful identification linearily syetem and nonlinearily system of relatively linearity.But for nonlinearily configuration relatively complexity system, We use genetic programming. Genetic programming is genetic algorithm expand, It use changing hiberarchy, but that use individual is length size alterable programe tree,it make complexity system delamination express.In this way genetic algorithm and genetic programming at resolve system identification receive successful application.