阀控非对称伺服缸基于粒子群优化的模糊PID控制器研究  

Fuzzy PID Controller Optimized by Particle Swarm Optimization for Valve Controlled Asymmetric Servo Cylinder

作　　者：丁问司[1,2] 刘坤 丁云柯[1,2] 

机构地区：[1]华南理工大学机械与汽车工程学院,广东广州510641 [2]韶关市华工高新技术产业研究院,广东韶关512027

出　　处：《液压与气动》2017年第9期17-23,共7页Chinese Hydraulics & Pneumatics

基　　金：国家自然科学基金(11272122);广东省部产学研重大项目(2012A090300011)

摘　　要：针对阀控非对称伺服缸非线性、参数时变的特点,考虑到油液压缩特性的影响,建立了包含变体积弹性模量的系统数学模型。提出一种基于粒子群算法优化(PSO)的模糊自适应PID控制方法(简称PSO_FPID)。模糊逻辑推理在线调整PID控制器的比例、积分和微分系数,以粒子群算法实现对模糊控制比例因子和量化因子的参数寻优,两种方法的组合保证了系统最佳参数匹配下的自适应控制。同时,利用AMESim与Simulink联合仿真研究不同含气量的阀控缸模型在传统PID与PSO_FPID两种控制方法下的动态响应特性。结果表明:PSO_FPID综合了PID控制器高精度的优点和模糊控制器快速、适应性强的特点,能够有效抑制油液动态压缩特性的非线性影响,使系统具有良好的动、稳态特性。According to the nonlinear and time-varying we establish the mathematical model of the system with of the oil compressibility. A fuzzy adaptive PID control is used to adaptively characteristics of the valve controlled asymmetric Cylinder, the variable effective bulk modulus considering the influence method optimized by the particle swarm optimization （PSO） adjust the proportion, integral and differential coefficient of the PID controller, and the PSO is aimed to optimize the scaling factors and the quantization factors of the fuzzy controller. The combination of two methods ensures the adaptive control of the system with the best parameters. At the same time, AMESim and Simulink are used to simulate the dynamic response characteristics of the valve con- trolled cylinder model with different air contents under two control methods of the traditional PID and PSO_FPID. The results show that the PSO-FPID, which combines the high precise advantage of the PID controller and the flexible character of the fuzzy controller, can effectively restrain the effect of nonlinear dynamic compression properties of the oil and enables the system to maintain a good dynamic and static quality.

关 键 词：模糊PID 粒子群算法 油液压缩特性 

分 类 号：TH137[机械工程—机械制造及自动化]