基于轮式里程计的无人车分层控制策略

Wheeled odometer based hierarchical control strategy for unmanned vehicle

中文关键词  无人车控制  轮式里程计  期望航向角  自抗扰控制  分层控制策略

英文关键词  unmanned vehicle control  wheeled odometer  expectation heading angle  active disturbance rejection control  hierarchical control strategy

中文摘要

      针对电动两驱差速型无人车,由于路面摩擦、车辆重心不稳等因素的存在,左右两侧驱动轮受到的行驶阻 力不同,导致车辆的行驶方向总是出现有规律的向左或者向右,偏离无人车纵轴线的现象.传统的无人车行驶方案 是靠图像、基站定位等方式根据外界的参考环境获得偏移误差,然后对车身进行调整,此类方法应对复杂环境的能 力有限.本文提出了一种基于自抗扰控制的仅依靠轮式里程计的无人车分层控制策略.首先,根据差速型无人车的 里程计信息推算出偏移的距离,上层控制器根据偏移期望航向角函数,调整车辆的航向角达到误差设计控制行驶的 目的. 下层控制器基于动力学模型设计的扩张状态观测器估计车辆运动产生的扰动以对两侧电机进行补偿.最后, 通过数值仿真和实车测试实验,验证了所提分层控制策略的有效性.

英文摘要

      For the electric two-drive differential unmanned vehicle, due to the existence of road friction, vehicle center of gravity instability and other factors, the driving resistance of the left and right driving wheels is different, resulting in the driving direction of the vehicle always deviates from the longitudinal axis of the unmanned vehicle regularly to the left or right. The traditional driving scheme of unmanned vehicles relies on images, base station positioning and other methods to obtain the offset error according to the external reference environment and then adjust the body. Such methods have limited ability to cope with the complex environment. This paper presents a hierarchical control strategy for unmanned vehicles based on active disturbance rejection control, which relies only on wheeled odometer. Firstly, the offset distance is calculated according to the odometer information of the differential unmanned vehicle, and the upper controller designs the expected course angle function according to the offset error, and adjusts the course angle of the vehicle to achieve the purpose of driving control. The lower controller designs an extended state observer based on the dynamics model to estimate the disturbance caused by vehicle motion and compensate the motors on both sides. Finally, the effectiveness of the proposed hierarchical control strategy is verified by numerical simulation and real vehicle test.