阀控非对称伺服缸基于粒子群优化的模糊PID控制器研究

发布时间：2018-06-27 23:19

本文选题：模糊PID + 粒子群算法　；参考：《液压与气动》2017年09期

【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。
[Abstract]:In view of the nonlinear and time-varying parameters of the valve controlled asymmetric servo cylinder, a system mathematical model including variable volume modulus of elasticity is established considering the influence of the compression characteristics of the oil. A fuzzy adaptive pid control method based on particle swarm optimization (PSO) is proposed. The proportion, integral and differential coefficients of pid controller are adjusted online by fuzzy logic reasoning, and the parameters of fuzzy control scale factor and quantization factor are optimized by particle swarm optimization algorithm. The combination of the two methods ensures the adaptive control under the optimal parameter matching of the system. At the same time, the dynamic response of the valve controlled cylinder model with different air content under the traditional pid and PSOFPID control methods is studied by using AMESim and Simulink. The results show that: PSOFPID combines the advantages of pid controller with high precision and fuzzy controller with the characteristics of fast and strong adaptability. It can effectively suppress the nonlinear effect of oil dynamic compression characteristics and make the system have good dynamic and steady characteristics.
【作者单位】：华南理工大学机械与汽车工程学院;韶关市华工高新技术产业研究院;
【基金】：国家自然科学基金(11272122) 广东省部产学研重大项目(2012A090300011)
【分类号】：TH137

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