摘要
A dynamic genetic algorithms based on numeric encoding is proposed and its application in system identification is discussed. Simulation shows that the introduction of both numeric encoding and dynamic mutation can effectively improve the accuracy and speed of searching for the optimum. It also show that the improved Genetic algorithm can identify time delay and parameters of the plant at the same time and converge to globle optimization.
A dynamic genetic algorithms based on numeric encoding is proposed and its application in system identification is discussed. Simulation shows that the introduction of both numeric encoding and dynamic mutation can effectively improve the accuracy and speed of searching for the optimum. It also show that the improved Genetic algorithm can identify time delay and parameters of the plant at the same time and converge to globle optimization.
