一种改进的液压伺服预测控制系统  

An Improved Predictive Control System for Hydraulic Servo

作　　者：戴永彬[1] DAI Yongbin(School of Software,Liaoning University of Technology,Jinzhou Liaoning 121000,China)

机构地区：[1]辽宁工业大学软件学院,辽宁锦州121000

出　　处：《机床与液压》2023年第1期101-106,共6页Machine Tool & Hydraulics

摘　　要：针对常规液压伺服系统的非线性、时滞等问题,提出一种基于多目标粒子群和类圆映射的液压伺服非线性预测控制系统(QCMPSO-NPC)。利用类圆映射技术将高维目标空间映射到二维坐标平面,监控粒子种群的进化状态。为平衡档案集的收敛性和多样性,采用面积支配和扇块距离管理档案集,并且根据种群进化状态自适应选择全局最优粒子。将改进算法应用到液压伺服系统中,系统可以准确追踪设定值。仿真实验结果表明:采用QCMPSO-NPC算法保证了解集的收敛性和多样性,输出响应最快,误差最小,位置跟踪性能优于PSO-NPC算法和GPC算法,验证了基于QCMPSO-NPC算法液压伺服控制系统的有效性和可行性。For the problem of nonlinearity and time-delay of traditional hydraulic servo system,a nonlinear predictive control system for hydraulic servo based on multi-objective particle swarm optimization and quasi-circular mapping(QCMPSO-NPC)was proposed.High dimensional target space was mapped to a 2-dimensional coordinate plot by the quasi-circular mapping in order to monitor evolutionary status of the particle population.In order to balance the convergence and diversity of the profiles,area-dominant and individual distance were used to manage the profiles,and the globally optimal particles were selected adaptively according to the population evolutionary state.The improved algorithm was applied to a hydraulic servo system and the set value could be tracked accurately by the system.The simulation experiment results show that:the convergence and diversity of the solution set can be ensured by using QCMPSO-NPC algorithm,it has the fastest output response and the least error,the position tracking performance is better than PSO-NPC algorithm and GPC algorithm.The effectiveness and feasibility of the hydraulic servo control system based on QCMPSO-NPC algorithm are verified.

关 键 词：粒子群优化 非线性预测 类圆映射 液压伺服系统 

分 类 号：TG334.9[金属学及工艺—金属压力加工] TP273[自动化与计算机技术—检测技术与自动化装置]