Path-following steering control for articulated vehicles

Passive steering systems have been used for some years to control the steering of trailer axles on articulated vehicles. These normally use a 'command steer' control strategy, which is designed to work well in steady-state circles at low speeds, but which generates inappropriate steer angles during transient low-speed maneuvers and at high speeds. In this paper, 'active' steering control strategies are developed for articulated heavy goods vehicles. These aim to achieve accurate path following for tractor and trailer, for all paths and all normal vehicle speeds, in the presence of external disturbances. Controllers are designed to implement the path-following strategies at low and high speeds, whilst taking into account the complexities and practicalities of articulated vehicles. At low speeds, the articulation and steer angles on articulated heavy goods vehicles are large and small-angle approximations are not appropriate. Hence, nonlinear controllers based on kinematics are required. But at high-speeds, the dynamic stability of control system is compromised if the kinematics-based controllers remain active. This is because a key state of the system, the side-slip characteristics of the trailer, exhibits a sign-change with increasing speeds. The low and high speed controllers are blended together using a speed-dependent gain, in the intermediate speed range. Simulations are conducted to compare the performance of the new steering controllers with conventional vehicles (with unsteered drive and trailer axles) and with vehicles with command steer controllers on their trailer axles. The simulations show that active steering has the potential to improve significantly the directional performance of articulated vehicles for a wide range of conditions, throughout the speed range. © VC 2013 by ASME.

Minimum maneuver time calculation using convex optimization

The problem of calculating the minimum lap or maneuver time of a nonlinear vehicle, which is linearized at each time step, is formulated as a convex optimization problem. The formulation provides an alternative to previously used quasi-steady-state analysis or nonlinear optimization. Key steps are: the use of model predictive control; expressing the minimum time problem as one of maximizing distance traveled along the track centerline; and linearizing the track and vehicle trajectories by expressing them as small displacements from a fixed reference. A consequence of linearizing the vehicle dynamics is that nonoptimal steering control action can be generated, but attention to the constraints and the cost function minimizes the effect. Optimal control actions and vehicle responses for a 90 deg bend are presented and compared to the nonconvex nonlinear programming solution. Copyright © 2013 by ASME.