Carbonell Rafael, Cuenca Ángel, Casanova Vicente, Pizá Ricardo, Salt Llobregat Julián J
Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain.
Sensors (Basel). 2021 Nov 13;21(22):7557. doi: 10.3390/s21227557.
In this paper, a two-wheel drive unmanned ground vehicle (UGV) path-following motion control is proposed. The UGV is equipped with encoders to sense angular velocities and a beacon system which provides position and orientation data. Whereas velocities can be sampled at a fast rate, position and orientation can only be sensed at a slower rate. Designing a dynamic controller at this slower rate implies not reaching the desired control requirements, and hence, the UGV is not able to follow the predefined path. The use of dual-rate extended Kalman filtering techniques enables the estimation of the fast-rate non-available position and orientation measurements. As a result, a fast-rate dynamic controller can be designed, which is provided with the fast-rate estimates to generate the control signal. The fast-rate controller is able to achieve a satisfactory path following, outperforming the slow-rate counterpart. Additionally, the dual-rate extended Kalman filter (DREKF) is fit for dealing with non-linear dynamics of the vehicle and possible Gaussian-like modeling and measurement uncertainties. A Simscape Multibody™ (Matlab/Simulink) model has been developed for a realistic simulation, considering the contact forces between the wheels and the ground, not included in the kinematic and dynamic UGV representation. Non-linear behavior of the motors and limited resolution of the encoders have also been included in the model for a more accurate simulation of the real vehicle. The simulation model has been experimentally validated from the real process. Simulation results reveal the benefits of the control solution.
本文提出了一种两轮驱动无人地面车辆（UGV）的路径跟踪运动控制方法。该无人地面车辆配备了用于感测角速度的编码器和一个提供位置与方位数据的信标系统。虽然速度可以快速采样，但位置和方位只能以较慢的速率进行感测。以这种较慢的速率设计动态控制器意味着无法达到期望的控制要求，因此，无人地面车辆无法跟踪预定义路径。使用双速率扩展卡尔曼滤波技术能够估计快速速率下不可用的位置和方位测量值。结果，可以设计一个快速速率动态控制器，该控制器利用快速速率估计值来生成控制信号。快速速率控制器能够实现令人满意的路径跟踪，其性能优于慢速速率控制器。此外，双速率扩展卡尔曼滤波器（DREKF）适用于处理车辆的非线性动力学以及可能的高斯型建模和测量不确定性。考虑到车轮与地面之间的接触力（这在无人地面车辆的运动学和动力学表示中未包含），已经开发了一个Simscape Multibody™（Matlab/Simulink）模型用于逼真的仿真。模型中还包含了电机的非线性行为和编码器的有限分辨率，以便更准确地模拟真实车辆。该仿真模型已通过实际过程进行了实验验证。仿真结果揭示了该控制解决方案的优势。
