湖南大学学报（自然科学版）2024，Vol.51Issue(5)：143-153,11.DOI:10.16339/j.cnki.hdxbzkb.2024056
基于改进遗传算法的磁流变阻尼半主动控制系统整体优化
Integrated Optimization of Semi-active Control System with Magneto-rheological Dampers Based on an Improved Genetic Algorithm
摘要
Abstract
To solve the optimization problem of control algorithm parameters,damper parameters,and layout location in the semi-active control systems with magnetorheological(MR)dampers,an improved adaptive niche genetic algorithm is proposed.The proposed genetic algorithm is improved in selection strategy,crossover and mutation operation,and adaptive adjustment of crossover probability and mutation probability.Two different niche technologies,the pre-selection mechanism and sharing mechanism,are used in the improved genetic algorithm.The results of a numerical example show that the optimization result of the improved adaptive niche genetic algorithm(GA-Ⅰ)and an improved simple genetic algorithm(GA-Ⅱ)is generally consistent,indicating the correctness of the former algorithm.Moreover,the GA-Ⅰ consumes an average of 32.7%less computation time to obtain the optimal solution for the first time than the GA-Ⅱ,which means that the former algorithm converges faster than the latter.In addition,optimization results of 30 times indicate that the GA-Ⅰ has stronger stability than the GA-Ⅱ.The semi-active control system with MR dampers optimized by the GA-Ⅰ achieves effective vibration suppression.The maximum values of inter-story drift angles and floor absolute accelerations of the semi-actively controlled structure under El Centro,Chi-Chi and man-made waves are decreased by 64.1%,54.7%,and 55.9%on average compared to those without control,respectively.The numerical example demonstrates the effectiveness of the GA-Ⅰ,and the integrated optimization of the semi-active control system with MR dampers is realized.关键词
磁流变阻尼器/半主动控制系统/整体优化/自适应小生境遗传算法Key words
magnetorheological damper/semi-active control system/integrated optimization/adaptive niche genetic algorithm分类
建筑与水利引用本文复制引用
梅真,张海龙,高毅超,陈业伟,李海锋..基于改进遗传算法的磁流变阻尼半主动控制系统整体优化[J].湖南大学学报（自然科学版）,2024,51(5):143-153,11.基金项目
国家自然科学基金资助项目(51778248),National Natural Science Foundation of China(51778248) （51778248）
福建省自然科学基金资助项目(2022J01291,2020J01057),Natural Science Foundation of Fujian Province(2022J01291,2020J01057) （2022J01291,2020J01057）
