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作 者:徐晓钦 陈志明 袁粤杨 沈萍 张镜洋 XU Xiaoqin;CHEN Zhiming;YUAN Yueyang;SHEN Ping;ZHANG Jingyang(College of Astronautics,Nanjing university of Aeronautics and Astronautics,Nanjing 211106,China)
出 处:《兵器装备工程学报》2025年第2期236-243,共8页Journal of Ordnance Equipment Engineering
摘 要:针对热电制冷器在温度控制过程出现超调量较大、误差较大等问题,提出一种基于改进型灰狼算法优化的BP神经网络动态整定PID控制参数的方法。在所提方法中使用差分进化法则对灰狼算法进行改进,使用经改进型灰狼算法优化后的BP神经网络对PID控制参数进行自适应调整。为验证该方法的有效性,对算法进行仿真并与Ziegler-Nichols调试法以及粒子群优化法进行控制效果对比。仿真结果表明,在连续实现1、5、10℃的温度目标过程中,所提方法相较于Ziegler-Nichols调试法、粒子群优化法在到温时间上分别减小了40.19%、1.54%,在超调量上分别减少了87.55%、69.14%,在稳态误差上分别减少了88.54%、67.23%。此外,在跟踪正弦函数目标的对比结果也进一步证实基于IGWO-BP-PID控制方法的优越性。所提方法可以快速、高精度地解决热电制冷器温度控制问题。To minimize overshoot and steady-state error in the control process of thermoelectric coolers reaching multi-temperature targets,this study proposes a control method based on improved Grey Wolf Optimizer(IGWO)optimized Back Propagation(BP)neural network algorithm.This method aims at adaptive tuning of PID control parameters.In this study,the Grey Wolf Algorithm is enhanced using differential evolution principles to improve the adaptive adjustment capability of BP neural networks for PID control parameters.To validate the efficiency of the proposed method,comparisons among the proposed method,the Ziegler-Nichols(ZN)tuning rule and the particle swarm optimization(PSO)algorithm,were conducted on the Simulink platform.The results indicated that,the ZN rule,the PSO algorithm and the IGWO-BP method exhibit settling times of 7.13 s,4.33 s and 4.27 s respectively,overshoots of 16.13%,6.51%,and 2.01%respectively,steady-state errors of 2.19e-3,0.77e-3 and 0.25e-3 respectively in achieving temperature of 1℃,5℃,and 10℃consecutively.The proposed method reduced the settling time,overshoot and steady-state error.Additionally,comparison results of sinusoidal function target tracking confirmed the superiority of the proposed method over the ZN rule and PSO algorithm in PID parameter tuning.The IGWO-BP-PID method provides a better choice for temperature control of thermoelectric coolers.
关 键 词:温度控制 热电制冷器 PID参数整定 BP算法 改进GWO算法
分 类 号:TP273.2[自动化与计算机技术—检测技术与自动化装置]
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