基于改进SOA算法自整定PID系统优化研究  

Research on Self-tuning PID System Optimization Based on Improved Seeker Optimization Algorithm

作　　者：葛育晓 赵荣珍[1] GE Yu-xiao;ZHAO Rong-zhen(School of Mechanical&Electronic Engineering,Lanzhou University of Technology,Lanzhou 730050,China)

机构地区：[1]兰州理工大学机电工程学院,甘肃兰州730050

出　　处：《仪表技术与传感器》2020年第10期108-113,116,共7页Instrument Technique and Sensor

基　　金：国家自然科学基金项目资助(51675253);兰州理工大学红柳一流学科建设项目支持

摘　　要：目前大多数工业控制工程都具有大时滞、非线性等特点,传统的PID控制算法难以取得较好的控制效果。针对这一问题,提出一种基于改进人群搜索算法的混沌自适应PID参数自整定算法,该算法采用惯性权重随机变异方式来确定步长,提出边界反射策略,避免传统算法中出界个体大量聚集在边界值的缺陷;并且引入了Logistic混沌思想,对最优解进行二次扰动,提高算法全局搜索能力。在Sphere等3个测试函数上将本文算法与多种知名算法进行对比,验证文中算法在求解的精度与收敛的速度上更优。最后,将本文算法运用于时滞非线性系统PID控制器参数优化。实验结果表明,改进的控制系统动态响应更快、鲁棒性更强、稳态精度更高。At present,most industrial control projects have the characteristics of large time lag,nonlinearity,and the traditional PID control algorithm is difficult to achieve better control results.Aiming at this problem,this paper proposes a chaotic adaptive PID parameter self-tuning algorithm based on improved crowd search algorithm.The algorithm uses the inertia weight random variation method to determine the step size,and proposes a boundary reflection strategy to avoid the large number of cross-border individuals in the traditional algorithm accumulating defects in boundary values,and the logistic chaos idea is introduced to perturb the optimal solution to improve the global search ability of the algorithm.In sphere and other three test functions,the algorithm of this paper is compared with a variety of well-known algorithms to verify that the algorithm is better in solving the accuracy and convergence speed.Finally,the algorithm is applied to the optimization of PID controller parameters of time lag nonlinear system.The experimental results show that the improved control system has faster dynamic response,stronger robustness and higher steady-state accuracy.

关 键 词：人群搜索算法 随机权重 边界反射 混沌 时滞非线性系统 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]