The current Proportion Integration Differentiation(PID) optimization design methods are often difficult to consider the system requirements for quickness,reliability and robustness.So an Improved Genetic Algorithm(IGA) is proposed.The new method of generating the initial population,adaptive change of crossover and mutation probability and effective selection strategy are used to optimize the parameters of PID controller. The simulation experiments with Matlab prove the new approach is valid.
Due to the disadvantages of genetic algorithm such as the weaker ability for local search, premature convergence, random walk and problems related, and so on , the design and improvement of the algorithm is an important research direction of genetic algorithm. And evaluating the performance of algorithm systematically and scientifically is the key to test algorithm whether good or bad .The common method used to evaluate algorithm is test function, however, the existing literature on the optimization algorithm has different methods to evaluate the performance of algorithm, and there is no uniform test criteria. As for those questions above, This paper studies test functions of genetic algorithm, and analyses characteristics of the main test functions, which can be used as the basis of selection algorithm test functions.
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