Improved Multi-objective Genetic Algorithm with Application to PID Optimization Design

We propose a multi-objective optimization genetic algorithm,which uses a new method to calculate crowding distance and improves the comparative method of non-domination.Double elitism-mechanism is introduced to improve efficiency of evolution and solution quality,and more effectively increase diversity of the solution.The algorithm is applied to optimal design of PID.In this way,the system is capable of considering requirements for quickness,reliability and robustness.A satisfactory solution is selected in Pareto optimum set according to the requirements of the present system.Simulation results indicate effectiveness of the proposed algorithm.