磁粉离合器自适应权重粒子群优化模糊控制的研究  

A Research on the Fuzzy Control of Magnetic Powder Clutch Based on Adaptive Weight Particle Swarm Optimization

作　　者：吴晓刚[1] 王旭东[1] 余腾伟[1] 

机构地区：[1]哈尔滨理工大学电气与电子工程学院,哈尔滨150040

出　　处：《汽车工程》2010年第6期510-514,523,共6页Automotive Engineering

基　　金：黑龙江省科技攻关项目(GB08A306);教育部科学技术研究重点项目(208180)资助

摘　　要：针对传统的模糊控制精度不高、自适应能力有限等问题,为了对车辆起步时磁粉离合器接合过程进行模糊控制,提出一种应用自适应权重粒子群优化算法来优化模糊控制器量化因子的方法。优化的量化因子将根据环境和负载的状况,实时跟踪模糊控制器参数的变化,从而提高了模糊控制器的鲁棒性和控制精度。仿真结果表明,与传统的模糊控制相比,采用自适应权重粒子群优化的模糊控制算法在降低发动机转速超调量的同时,减小了车辆起步的最大冲击度和离合器接合过程中的滑摩功。Aiming at the problems of traditional fuzzy control such as poor accuracy and limited adaptive ca- pability and for implementing fuzzy control in the engagement process of magnetic powder clutch in vehicle starting, a method of using adaptive weight particle swarm optimization algorithm to optimize the quantizing factor of fuzzy controller is proposed. The quantizing factors optimized will track the change of fuzzy controller parameters according to the circumstance and loading conditions, and hence the robustness and control accuracy of fuzzy controller are im- proved. The simulation results show that compared with traditional fuzzy control, using fuzzy control algorithm with adaptive weight particle swarm optimization will reduce the maximum jerk in vehicle starting and the friction work in clutch engagement process, while decreasing the overshoot of engine speed.

关 键 词：磁粉离合器 粒子群优化 模糊控制 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]