基于粒子群的压电结构多目标同步优化控制

为了分析压电智能结构振动主动控制中结构与控制的耦合特性，克服现用优化算法的复杂性，以压电智能梁结构为研究对象，运用粒子群优化方法对传感器与作动器分布和反馈控制增益进行同步优化.选用储存能量和控制能量最小以及振动衰减最快的多重性能指标作为优化目标函数，找出了针对特定振动模态下的最佳贴片位置与控制增益，分析了压电片长度和数量对控制效果的影响.运算结果表明，与传统遗传算法相比，粒子群具有编程简单、计算量小、收敛速度快等优点.仿真结果显示，基于粒子群同步优化后的结构振动控制效果明显，验证了该方法的可行性.

Multi-objective simultaneous optimization control for piezoelectric structure based on particle swarm

In order to analyze the coupling characteristics of structure and control in the active control of piezoelectric smart structure vibration and overcome the complexity of existing optimization algorithms,a piezoelectric smart beam was chosen as the research object,and a particle swarm optimization(PSO) method was used to carry out the simultaneous optimization for the arrangement of sensors and actuators as well as the feedback control gains.A multiple performance index with the minimum storage energy and control energy as well as the fastest vibration decay was selected as an optimum objective function.The optimal piezoelectric patch positions and control gains at specific vibration modes were found out.In addition,the influence of both length and number of piezoelectric patches on the control effect was analyzed.The calculated results show that compared with the traditional genetic algorithm,the particle swarm method has such advantages as simple programming,small calculation amount and fast convergence speed.The simulated results show that with the simultaneous optimization based on particle swarm,the control effect for structure vibration is obvious,and the feasibility of the proposed method is proved.