Observational analysis improved trajectory tracking in an electric vehicle, indicating robust control for actuator dynamics.
This research presents the design of a robust nonlinear controller for the lateral dynamics of a self-driving car. It is based on the block control and super-twisting sliding mode control techniques in order to effectively mitigate the uncertainties and disturbances of the vehicle. The dynamic model of the system is composed of the standard bicycle dynamic model (not kinematic) for the vehicle and the dynamics of a BLDC motor connected to a steering rack system as the steering actuator. Moreover, the control scheme considers an inner loop for controlling the actuator position based on the field-oriented control (FOC) and PID control approaches. The controller’s overall performance is validated through its application to a mathematical model of a brushless direct current (BLDC) motor, acting as the actuator, plus the steering rack dynamics and the lateral dynamic model of the vehicle. Measurements of voltages and currents are taken in both the abc and dq reference frames, the latter being commonly used in the field-oriented control (FOC) technique. Additionally, the system’s performance is evaluated in terms of trajectory tracking, orientation, and lateral deviation from the lane center.
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Torres-Romero et al. (2025) studied this question.
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