MPC-based Approach to Optimized Steering for Minimum Turning Radius and Efficient Steering of Multi-axle Crane

Abstract

In a conventional steering system for a multi-axle crane, the steering angle of each axle is determined according to Ackernianns steering principle,'which assumes the slip angles of the tires are negligible. The role of optimal steering control in improving a driver's steering efficiency is hardly considered in Ackermann's principle. To address this problem, this paper proposes a control strategy for determining the optimal steering angles for a multi-axle crane and thereby improving a driver's steering efficiency by applying the model predictive control (MPC) algorithm and defining a driver's intentions. A simplified crane model for the steering system was developed using a bicycle model, and a comparative study was carried out via simulation to analyze steering performance for the conventional (Ackermann) and proposed steering control systems for the cases of all-wheel steering and road steering modes. The simulation results show that both the minimum turning radius and the driver's steering effort are decreased more by the proposed steering control system than by conventional system and that the proposed control strategy therefore yields better steering performance.