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基于AGA的智能桁架结构模糊振动控制
引用本文:张京军,段瑶瑶,高瑞贞. 基于AGA的智能桁架结构模糊振动控制[J]. 河北工程大学学报(自然科学版), 2016, 33(2): 5-9
作者姓名:张京军  段瑶瑶  高瑞贞
作者单位:河北工程大学 机电工程学院, 河北 邯郸 0560382;河北工程大学 土木工程学院, 河北 邯郸 056038;河北工程大学 机电工程学院, 河北 邯郸 0560382
基金项目:国家自然科学基金资助项目(11302066和11272112)
摘    要:应用一种根据适应度自动调整选择交叉概率和变异概率的自适应遗传算法(Adaptive Genetic Algorithm,简称AGA),来优化智能桁架结构模糊控制系统。首先,考虑到压电主动杆的机电耦合特性,建立系统的有限元动力方程;其次,以智能桁架结构的主动杆轴向位移差为优化目标,使用自适应遗传算法优化模糊控制规则,以增强智能桁架结构模糊控制器的振动控制效果;利用Matlab/Simulink建立空间智能桁架结构的仿真模型,对模糊规则优化前后的控制结果进行对比。仿真结果表明:使用自适应遗传算法优化后的模糊控制器,能够加快智能桁架振动衰减速度,并且有效消除模糊控制的稳态误差。

关 键 词:自适应遗传算法  智能桁架  模糊规则  主动振动控制  Matlab
收稿时间:2015-12-18

Fuzzy control for intelligent truss structure based on AGA
ZHANG Jingjun,DUAN Yaoyao and GAO Ruizhen. Fuzzy control for intelligent truss structure based on AGA[J]. Journal of Hebei University of Engineering(Natural Science Edition), 2016, 33(2): 5-9
Authors:ZHANG Jingjun  DUAN Yaoyao  GAO Ruizhen
Affiliation:Mechanical and Electrical Engineering Institute. Hebei University of Engineering, Hebei Handan 056038, China;College of Civil Engineering, Hebei University of Engineering, Hebei Handan 056038, China;Mechanical and Electrical Engineering Institute. Hebei University of Engineering, Hebei Handan 056038, China
Abstract:In this paper, an adaptive genetic algorithm (AGA) which can adaptively select crossover probability and mutation probability is presented to optimize the fuzzy control system for the space intelligent truss structure. Firstly, considering the electromechanical coupling characteristic of piezoelectric active bars, the finite element dynamic equations of the system are established. Secondly, the optimization goal is the minimum of axial displacement difference of intelligent truss active bars. An adaptive genetic algorithm is applied to optimize fuzzy control rules to improve the control effect of fuzzy controller of intelligent truss structure. To demonstrate the effectiveness of this method, the model of space intelligent truss structure is established by the Matlab/Simulink simulation, and the control results of fuzzy rules before and after optimization are compared. Simulation results show that after the optimization with adaptive genetic algorithm, the intelligent truss vibration damping rate has also been accelerated, and the steady-state error of fuzzy control are effectively eliminated.
Keywords:adaptive genetic algorithm  intelligent truss  fuzzy rules  active vibration control  Matlab
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