Improved Adaptive Genetic Algorithm and its Application Research in Parameter Identification

Abstract

An improved adaptive genetic algorithm(IAGA) was proposed to avoid the premature problem and the slow convergence.Through the experiment of a typical Needle-in-a-haystack problem,the proposed algorithm shows its better global optimal ability and its faster convergence ability.Based on the above,the improved algorithm was applied to identify system parameter.The identification results show that this method has the advantages of high parameter identification precision,strong ability of resistance to the noise,good input signal generality and identification of the nonlinear system,so it has important practical values.