摘要
根据履带车辆转向运动学和动力学分析,提出转向控制策略,可在满足系统压力限制以及保证车辆转向安全条件下自动降低平均车速以保证驾驶员期望转向半径的准确实现。转向控制器由神经网络PID控制器和泵马达排量控制器组成。运用Matlab/Simulink对系统进行神经网络转向控制仿真分析,仿真结果表明,与传统PID控制相比较,神经网络控制输出超调量由10.5%降至4.1%,控制响应时间由4.8 s降至2.2 s,提高了系统实时性和鲁棒性。不同转向工况的仿真结果表明,采用神经网络控制可使静液驱动履带车辆获得良好的转向稳定性和操纵性。
Based on steering kinematics and dynamics analysis of tracked vehicle,steering control strategy was presented to realize reducing average vehicle speed automatically while achieving the driver＇s expected steering radius exactly in the case of not exceeding the system pressure threshold and secure steering.The steering controller was comprised of neural network PID controller and pump motor displacement controller.The steering neural network control simulation was conducted by using Simulink of Matlab.The simulation results indicated that compared with conventional PID control,neural network control export overshoot reduced from 10.5% to 4.1% and control response time decreased from 4.8s to 2.2s,which meant that system real-time ability and robustness were improved.The simulation results for various steering conditions demonstrated that good steering stability and maneuverability were obtained with neural network control for tracked vehicle with hydrostatic drive.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2010年第7期15-20,共6页
Transactions of the Chinese Society for Agricultural Machinery
基金
国防预先研究支撑项目(62301030303)
高等学校学科创新引智计划资助项目(B08043)
关键词
履带车辆
静液驱动
转向
神经网络
PID控制
Tracked vehicle
Hydrostatic drive
Steering
Neural network
PID control
