Skid Steering-Based Control of a Robotic Vehicle with Six in-Wheel Drives

Abstract

This paper describes a driving control algorithm based on a skid steering for a robotic vehicle with articulated suspension (RVAS). The RVAS is a kind of unmanned ground vehicle based on a skid steering using an independent in-wheel drive at each wheel. The driving control algorithm consists of four parts: a speed controller for following a desired speed, a lateral motion controller that computes a yaw moment input to track a desired yaw rate or a desired trajectory according to the control mode, a longitudinal tyre force distribution algorithm that determines an optimal desired longitudinal tyre force, and a wheel torque controller that determines a wheel torque command at each wheel in order to keep the slip ratio at each wheel below a limit value as well as to track the desired tyre force. Longitudinal and vertical tyre force estimators are required for the optimal tyre force distribution and wheel slip control. A dynamic model of the RVAS for simulation study is developed and validated using the vehicle test data. Simulation and vehicle tests are conducted in order to evaluate the proposed driving controller. It is found from simulation and vehicle test results that the proposed driving controller provides a satisfactory motion control performance according to the control mode.

Handling performance control for hybrid 8-wheel-drive vehicle and simulation verification

“…For some previous researches, [6][7][8] the handling performance control strategy was only analysed by a vehicle body dynamic model with tyre mechanical properties to investigate the vehicle handling behaviour. Apparently, for a hybrid vehicle, the handling performance control system has a great influence on the performance of electricity elements, such as State of Charge (SOC), which should also be focused on.…”

“…As known, the adhesion capability is in proportion to the vertical force acting on the tyre. The calculation of the vertical force on each tyre is based on the common load transfer calculation method, [7] with the help of longitudinal and lateral acceleration sensors.…”

“…In recent years, many methods were proposed to decrease the minimum steer radius of the armoured wheeled vehicle, such as skid steer technology. [7,27] The skid steered vehicle is steered by the difference of rotation speed and torque between two side wheels, it can achieve pivot steer like tracked vehicle, but the handling performance is poor and the slip condition of tyre is much worse. [7] Based on the configuration proposed in Section 2, the minimum steer radius can also been decreased.…”

“…[1][2][3][4] Among different kinds of configurations, the handling performance of HEVs equipped with independent motors can be further improved because of the direct yaw control (DYC). [5][6][7][8] Based on above advantages, the technology of hybrid electric distributed motor drive has been used in armoured vehicle area because of the great demand of operational radius and mobility.…”

Dynamic Control for Unmanned Skid-steering Vehicle with Conditional Integartors

“…问题。 南昌航空大学的吴剑等 [6] 根据运动学模型，基 于李雅普诺夫函数，采用反推设计方法，从而实现 差动转向轮式机器人轨迹跟踪控制， 在控制过程中， 采取速度和加速度受限策略，以保证机器人运动的 平滑和稳定。常江等 [7] 提出了一种新的非完整轮式 移动机器人轨迹跟踪控制的滑模控制方法，并利用 极坐标系进行滑膜面的选择以使得滑模控制器可以 对外部扰动进行补偿，并给出了该方法基于李雅普 诺夫稳定性的分析。 显然，对于差动转向形式的无人车研究大部分 集中在运动控制方面，考虑如何实现车辆对轨迹的 跟踪，但是在给定轨迹下实现差动转向车辆期望横 摆角速度和期望车速的的动力学控制研究比较少。 LUCER 等 [8] 在给定的轨迹下通过分别针对转向和 直线行驶，设计滑模控制算法，实现差动转向车辆 横摆角速度和车速的跟踪控制，从仿真验证上看有 效改善了路面和轮胎之间的不确定性。KANG 等 [9] 对六轮独立驱动的差动转向车辆进行了研究，采用 了分层式的的控制结构，直接通过轮胎力来提供横 摆力矩， 实现车辆的横摆角速度和车速的跟踪控制。 KOZLOWSKI 等 [10] 设计了考虑车辆动力学参数不 确定的鲁棒控制算法。但是在动力学控制方面基本 上都缺乏考虑车轮滑移以及执行器力矩受限对车辆 控制的影响。 由于差动转向车辆一般工作在复杂的地形环 境，轮胎滑移现象不能被忽视。其次轮胎打滑以及 地形环境的不确定性会导致差动转向车辆的执行器 力矩饱和，进一步使车辆失稳。因此，本文在原有 研究基础上 [11] T 为液压制动 力作用在差速器右端的制动力矩。 …”