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Abstract
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.
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