In this paper, a steering control system for the path tracking of autonomous vehicles is described. The steering control system consists of a path tracker and primitive driver. The path tracker generates the desired steering angle by using the look‐ahead distance, vehicle heading, and a lateral offset. A method for applying an autonomous vehicle to path tracking is an advanced pure pursuit method that can reduce cutting corners, which is a weakness of the pure pursuit method. The steering controller controls the steering actuator to follow the desired steering angle. A servo motor is installed to control the steering handle, and it can transmit the steering force using a belt and pulley. We designed a steering controller that is applied to a proportional integral differential controller. However, because of a dead band, the path tracking performance and stability of autonomous vehicles are reduced. To overcome the dead band, a dead band compensator was developed. As a result of the compensator, the path tracking performance and stability are improved.
With the development of electro-hydraulic brake system in the automotive application, pressure control is at the top of a brake system engineer’s agenda. This work focuses on the development of a pressure-loop controller for a motor-type electro-hydraulic brake system, which is composed of an electro-mechanical actuator and a hydraulic link. The pressure control issue of motor-type electro-hydraulic brake system is influenced intensely by the nonlinearities (i.e. friction) and uncertainties (e.g. temperature variation, brake pad wear, and so on) of the system and by the very demanding performance specifications (i.e. supporting cooperative work with hydraulic control unit of anti-lock brake system). The pressure control of motor-type electro-hydraulic brake system is investigated, and a novel pressure–based control strategy via fusion of control signals is proposed to improve the pressure tracking performance. The control strategy comprises online model–based friction compensation, online dither–based friction compensation, and feedback control. Four original contributions make this work distinctive from the existing relevant literature. Selecting the Coulomb+viscous friction model can maximize to reduce difficulty of parameter identification and Stribeck effects detection based on maintaining the pressure tracking accuracy. Thanks to the model-based friction compensation torque, the signal magnitude of dither-based friction compensation torque can be decreased so that the vehicle comfort can be improved. The compensation parameters of both the model-based and dither-based friction compensation can be online modified according to the operating point of system. The robustness of the fusion controller is enhanced by employing the sliding mode control algorithm with conditional integrator. The performance of the proposed control strategy is evaluated by hardware-in-the-loop-simulation and vehicle experiment in typical braking situations. The experimental results with fusion control show improved pressure tracking performance in comparison with that without fusion control.
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