电子差速履带车辆转向转矩神经网络PID控制  

Neural Networks PID Control of Steering Torque for Electronic Differential Tracked Vehicle

作　　者：翟丽[1] 孙逢春[1] 谷中丽[1] 

机构地区：[1]北京理工大学机械与车辆工程学院,北京100081

出　　处：《农业机械学报》2009年第2期1-5,31,共6页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家部委预研项目(40402070104);国家"863"高技术研究发展计划资助项目(2007AA11A105)

摘　　要：根据电子差速履带车辆转向动力学和运动学分析,提出一种电子差速履带车辆转向转矩模拟神经网络PID(ANNPID)控制策略,由双电动机转向转矩协调控制、ANNPID控制和感应电动机转矩控制组成。通过建立双感应电动机独立驱动履带车辆电子差速转向控制系统,实现基于ANNPID控制的转向转矩协调分配和基于模型参考自适应控制(MRAC)的感应电动机间接磁场定向(IFOC)转矩控制。采用该策略,在不同转向半径的行驶转向工况、0.5B半径转向工况和中心转向工况下的实车试验结果表明,低速转向具有较好的操控性能。According to kinematics and dynamics of tracked vehicle, an analog neural networks PID （ANNPID） control strategy of steering torque for electronic differential tracked vehicle was proposed. The ANNPID control strategy consisted of integrated torque control of two motors, ANNPID control and torque control of an induction motor. A steering control system scheme of electronic differential tracked vehicle with dual induction motors and independent driven was established to achieve torque distribution between two motors based on ANNPID and indirect rotor field oriented （IFOC）torque control of induction motor based on model reference adaptive control（MRAC）. Experimental results of dual motors for running steering with different steering radius, 0.5B radius steering and center steering situation showed the effectiveness of the strategy, and indicated that electronic differential tracked vehicle in low-speed has good steering maneuverability.

关 键 词：履带车辆 转向 电子差速 转矩控制 神经网络PID控制 

分 类 号：U469.694[机械工程—车辆工程] TP273[交通运输工程—载运工具运用工程]