高级检索
代晨曦,周方伟,卫晓娟. 基于PSO优化的一类碰撞振动系统混沌控制[J]. 应用技术学报,2022,22(3):270-275.. DOI: 10.3969/j.issn.2096-3424.2022.03.013
引用本文: 代晨曦,周方伟,卫晓娟. 基于PSO优化的一类碰撞振动系统混沌控制[J]. 应用技术学报,2022,22(3):270-275.. DOI: 10.3969/j.issn.2096-3424.2022.03.013
DAI Chenxi, ZHOU Fangwei, WEI Xiaojuan. Chaos Control for A Class of Vibro-Impact System Based on PSO Optimization[J]. Journal of Technology, 2022, 22(3): 270-275. DOI: 10.3969/j.issn.2096-3424.2022.03.013
Citation: DAI Chenxi, ZHOU Fangwei, WEI Xiaojuan. Chaos Control for A Class of Vibro-Impact System Based on PSO Optimization[J]. Journal of Technology, 2022, 22(3): 270-275. DOI: 10.3969/j.issn.2096-3424.2022.03.013

基于PSO优化的一类碰撞振动系统混沌控制

Chaos Control for A Class of Vibro-Impact System Based on PSO Optimization

  • 摘要: 针对一类含间隙单自由度刚性碰撞振动系统的混沌运动控制问题,提出一种基于PSO优化RBF神经网络控制器的参数反馈混沌运动控制方法。分析了混沌运动与激励频率变化之间的关联关系及表现特征,总结了分岔及混沌运动的参数分析判据,并据此设计了RBF神经网络参数反馈混沌控制器;构建了以Poincaré截面上相邻2点距离最小为目标的适应度函数,以引导PSO算法优化控制器的参数;通过给系统可控参数施加一个小扰动,达到将混沌运动控制为稳定周期运动的目的。该方法可适用于模型未知或难以建立精确数学模型的混沌运动控制。仿真结果验证了该控制方法的可行性及有效性。

     

    Abstract: In view of the chaos control problem for a single-degree-of-freedom vibro-impact system with clearance, a parameter feedback control method of chaotic motion based on radial basis function neural network (RBFNN) optimized by particle swarm optimization(PSO) was proposed. Firstly, the correlation relationship and its performance characteristics between chaotic motion and excitation frequency change were analyzed, and the parameter analysis criteria of bifurcation and chaotic motion were summarized. Then, a parameter feedback chaotic controller of radial basis function (RBF) neural network was designed on the basis of the analysis. Secondly, a fitness function aiming at minimizing the distance between two adjacent points on the Poincaré section was constructed to guide the PSO algorithm to optimize the parameters of the controller. Finally, a small perturbation was applied to the controllable parameters of the system to control the chaotic motion as a stable periodic motion. This method can be applied to chaotic motion control where the model is unknown or the precise mathematical model is difficult to establish. The feasibility and effectiveness of the proposed control method were verified by simulation results.

     

/

返回文章
返回