LQR-based adaptive steering control algorithm of multi-axle crane for improving driver's steering efficiency and dynamic stability

摘要

The conventional steering principle (Ackerman theory) for existing steering systems of a multi-axle cane determines the steering angle of each axle by focusing on minimizing the slip angles rather than enhancing a driver's steering efficiency. Therefore, this paper proposed a LQR-based adaptive steering control algorithm of a multi-axle crane which solves the optimal steering angles to improve the driver's steering efficiency. For this, a crane error dynamics model was derived and simulation studies were conducted to evaluate the proposed controller's performance for the cases of single-lane-change and curved path scenarios. The simulation results present that the proposed steering control strategy improves the steering efficiency by decreasing the driver's steering effort, and dynamics stability by reducing the yaw rate.