CAJ | 학술논문

该文提出一种多目标遗传算法,采用新的拥挤距离计算方法,改进非支配性的比较方法.并引入双重精英策略,提高了进化效率和解的质量,更有效地保持了解的多样性.将该算法应用于PID优化设计,使系统可同时兼顾快速性、稳定性和鲁棒性,决策者可根据当前工作需求在所得的Pareto解集中选择最终的满意解.仿真结果表明提出的设计方法有效.
해문제출일충다목표유전산법,채용신적옹제거리계산방법,개진비지배성적비교방법.병인입쌍중정영책략,제고료진화효솔화해적질량,경유효지보지료해적다양성.장해산법응용우PID우화설계,사계통가동시겸고쾌속성、은정성화로봉성,결책자가근거당전공작수구재소득적Pareto해집중선택최종적만의해.방진결과표명제출적설계방법유효.
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.