Parameters Identification of Continuous System Based on Hybrid Genetic Algorithm

A new hybrid genetic algorithm is provided by adding up the advantages of the genetic algorithm and gradient algorithm, as uses the results of gradient algorithm improving the populations of genetic algorithm, and selects the best point as the start point of gradient algorithm next time by comparing the best point of genetic algorithm with the last results of gradient algorithm. Applying the method to estimating the parameters of continuous system, the simulation results show it is more quickly than genetic algorithm and owes better anti-noise ability, and improves the defects of genetic algorithm with slower searching ability near a point, and it provides a new method for the parameters estimation of continuous system.