摘要
针对大型卧式液压仿真转台内部双液压马达摩擦力矩干扰、负载干扰和外框双液压马达同步驱动这三个影响转台控制性能的主要问题,分析并总结出转台外框双液压马达在“等同模式”和“主从模式”下的同步驱动模糊控制规则、各种同步控制模式的应用范围和切换规律;根据PID控制经验制定出直接自适应模糊控制规则。依据同步与PID模糊控制规则设计出同步-干扰模糊控制器并进行仿真分析。针对模糊控制器自学习能力较差等缺陷,在模糊控制的基础上,采用模糊神经网络(FNN)模型设计出多输入多输出(MIMO)的转台FNN控制器。软件仿真结果表明,当转台液压马达摩擦力矩发生变化、负载大范围波动或当转台外框两马达转速相差较大时,使用模糊神经网络模型的智能化转台控制系统具有较高的定位精度和动态性能。
For friction ofhyraulic motors, disturbance from load and synchronizing drive of outer gimbal dual hyraulic motors which are three primary factors affected on performance of hydraulic simulating rotary-table, analysis and summarize fuzzy control rules for synchronizing drive of outer gimbal and rules switch on different control models, fuzzy control rules include equation rules and principal and subordinate rules; Establish direct adaptive fuzzy controller（DAFC） based on PID control experiences, present synchronization--disturbance fuzzy controller. Since the deficiency of poor ability of self-learning of fuzzy controller, fuzzy neural net（FNN） controllers for multi-input multi-output （MIMO） system are induced to the above two fuzzy controllers to resolve this problems, and used to noliner system is more suitable Simulation results of FNN controllers show that the proposed approach can achieve high displacement tracking accuracy and dynamic performance when the loads of the simulating rotary-table are changeable or two hydraulic motors＇ rotate speeds are different greatly.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2006年第10期233-238,共6页
Journal of Mechanical Engineering
关键词
三轴转台
摩擦
干扰
同步驱动
模糊控制
模糊神经网络
Three gimbals rotary table Friction, Disturbance Synchronizing driver, Fuzzy controller Fuzzy neural net（FNN）
