基于MPSO的电液举升伺服系统自适应模糊PID控制

为提高电液举升伺服系统位置控制精度,提出一种基于改进的粒子群算法(MPSO)优化的自适应模糊PID控制策略。根据流体动力学原理,建立伺服阀控非对称缸系统数学模型,分析系统动态运动特性。综合考虑多种不确定扰动影响,设计自适应模糊PID(AF-PID)控制器,并通过MPSO算法对AF-PID控制器中的量化因子和比例因子进行迭代寻优。利用MATLAB/Simulink和AMESim仿真软件,搭建系统的联合仿真模型,并对所设计控制器的控制性能进行仿真验证。结果表明:相同工况下,相较于常规PID和AF-PID控制器,MPSO-AF-PID控制器作用下系统的轨迹跟踪性能最优,能更好地满足起下管柱作业需求。

Adaptive Fuzzy PID Control of Electro hydraulic Lifting Servo System Based on MPSO

In order to improve the position control accuracy of electro-hydraulic lifting servo system, an adaptive fuzzy PID control strategy based on the improved particle swarm optimization (MPSO) was proposed. According to the principle of hydrodynamics, the mathematical model of the servo valve controlled asymmetric cylinder system was established, and the dynamic characteristics of the system were analyzed. By considering the influence of various uncertain disturbances, an adaptive fuzzy PID (AF-PID) controller was designed, and the quantization factor and proportion factor in the AF-PID controller were optimized iteratively through MPSO algorithm. MATLAB/Simulink and AMESim simulation software were used to build the joint simulation model of the system, and the control performance of the designed controller was verified by simulation. The results show that compared with conventional PID controller and the AF-PID controller, the MPSO-AF-PID controller greatly improves the trajectory tracking performance of the system, which can better meet the requirements of the tripping operation.