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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
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Integrated Optimization of Semi-active Control System with Magneto-rheological Dampers Based on an Improved Genetic Algorithm
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    摘要:

    为解决磁流变阻尼半主动控制系统中控制算法参数、阻尼器参数与布置位置优化问题,提出一种改进的自适应小生境遗传算法.该遗传算法在选择策略、交叉和变异操作、交叉概率和变异概率的自适应调整等方面作了改进,并同时采用预选择机制和共享机制这两种小生境技术.算例分析结果表明:改进的自适应小生境遗传算法和改进的基本遗传算法优化结果总体一致,表明前者分析结果是正确的;前者首次得到最优解耗费的机时比后者平均少32.7%,可见前者比后者收敛速度更快;30次优化分析结果表明,前者比后者稳定性更强;经前者优化的磁流变阻尼半主动控制系统取得良好减振效果,El Centro波、集集波、人工波输入时,半主动控制结构层间位移角和绝对加速度的最大值较无控时分别平均减小64.1%、54.7%、55.9%.算例表明了改进的自适应小生境遗传算法的有效性,实现了对磁流变阻尼半主动控制系统的整体优化.

    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.

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MEI Zhen?,ZHANG Hailong, GAO Yichao, CHEN Yewei, LI Haifeng.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,(5):143~153

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  • 在线发布日期: 2024-05-30
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