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Model Predictive Control Allocation of an Over-actuated Electric Vehicle with Single Wheel Actuators

机译:单轮执行器的过腐斗电动车辆模型预测控制分配

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The scope of this paper is the development of a model predictive control allocation (MPCA) algorithm for over-actuated electric vehicles with individually steered and driven wheels. The presented algorithm utilizes a physical white-box model of the steering, drive and tire dynamics for the distribution of the control commands. Thereby, the actuator dynamics and constraints on the state variables as well as the control and output variables are taken into account. The optimization, based on the linearized underlying dynamics considered with slowly time varying wheel velocities, allows different driving situations. For the vehicle’s motion, a nonlinear model predictive motion controller (NMPC) is presented. The control strategy is successfully tested in simulations without restrictions on the desired longitudinal, lateral or yaw dynamics of the vehicle.
机译:本文的范围是开发用于具有独立转向和驱动的车轮的过致动电动车辆的模型预测控制分配(MPCA)算法。所提出的算法利用转向,驱动器和轮胎动力学的物理白盒模型,用于分布控制命令。由此,考虑了致动器动态和对状态变量以及控制和输出变量的约束。基于用缓慢时间不同的车轮速度考虑的线性化底层动态的优化允许不同的驾驶情况。对于车辆的运动,呈现了非线性模型预测运动控制器(NMPC)。控制策略在模拟中成功测试,而不限制车辆的所需纵向,横向或偏航动态。

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