基于PSO-BPNN算法的红外连续变焦镜头伺服控制系统参数整定

Parameter Tuning of Infrared Continuous Zoom Lens Servo Control System Based on PSO-BPNN Algorithm

  • 摘要: 针对传统红外连续变焦镜头伺服控制系统参数整定动态性能不佳、灵活性差和效率低的问题,本文研究了一种PSO-BPNN算法整定红外连续变焦镜头伺服控制系统参数的方法。首先通过系统识别法建立红外连续变焦镜头伺服控制系统动态数学模型,同时建立PSO-BPNN算法模型,然后进行PSO-BPNN算法整定红外连续变焦镜头伺服控制系统控制器参数仿真实验,最后搭建实验性能测试平台进行实验和验证。仿真与性能测试实验结果表明:上升时间tr≤0.055 s,调节时间ts≤0.26 s,超调量σ≤27.6%,红外连续变焦镜头伺服控制系统反应速度快、稳定性好且目标跟随精度高。

     

    Abstract: In responsed to the problems of poor flexibility, low utilization of system dynamic performance, and low efficiency in traditional infrared continuous zoom lens servo control system parameter tuning methods, this paper studied a PSO-BPNN algorithm for tuning parameters of the system. Firstly, a dynamic mathematical model of the system was established by the system identification method. At the same time, a PSO-BPNN algorithm model was established, followed by simulation experiments. Finally, an experimental performance testing platform was built for experiments. The simulation and performance testing experimental results had shown that: rise time tr≤0.055 s, settling time ts≤0.26 s, overshoot σ≤27.6%, the system had fast response speed, good stability, and high target tracking accuracy.

     

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