摘要
针对随动系统模糊控制中量化和比例因子等参数的选取过于依赖经验、缺乏规范的缺陷,提出一种基于遗传与粒子群混合算法的参数优化方法,大幅降低系统的跟踪误差并优化系统的动态特性,有效克服波动力矩扰动等非线性因素的影响,使系统基本满足非线性、时变性控制的要求,并通过仿真验证该方法的有效性。
In servo system fuzzy control,aiming at the defects of the selection of parameters including scale factors and quantitative factors,which depends on experience too much and lacks standardization,proposed was a parameter optimization method based on genetic and particle swarm. Not only can this method greatly reduce the tracking error and optimize dynamic characteristics of the system,it can also effectively overcome the influence of nonlinear factors from wave moment disturbances. This method makes the system basically satisfy the control requirements of nonlinear and time-varying. The fine controlled effects of the proposed method are verified through simulation.
作者
程文鑫
赵博伟
姜尚
CHEN Wenxin1, ZHAO Bowei2, JIANG Shang3(1. Naval Ordnance Equipment Bureau, Beijing 100080, China; 2. Xi＇ an Bureau of Naval Equipment Department, Xi＇ an 710043, Shaanxi,China; 3. Department of Weapon Engineering, Naval University of Engineering, Wuhan 430033 Hubei,Chin)
出处
《火炮发射与控制学报》
北大核心
2018年第2期61-64,74,共5页
Journal of Gun Launch & Control
关键词
控制理论
粒子群
模糊控制
参数优化
servo system
particle swarm
fuzzy control
parameter optimization
