Active steering

Abstract: In this paper a novel approach to autonomous steering systems is presented. A model predictive control (MPC) scheme is designed in order to stabilize a vehicle along a desired path while fulfilling its physical constraints. Simulation results show the benefits of the systematic control methodology used. In particular we show how very effective steering manoeuvres are obtained as a result of the MPC feedback policy. Moreover, we highlight the trade off between the vehicle speed and the required preview on the desired path in order to stabilize the vehicle. The paper concludes with highlights on future research and on the necessary steps for experimental validation of the approach.

Abstract: A Model Predictive Control (MPC) approach for controlling an Active Front Steering (AFS) system in an autonomous vehicle is presented. At each time step a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to best follow the desired trajectory on slippery roads at the highest possible entry speed. We start from the results presented in [2], [6] and formulate the MPC problem based on successive on-line linearization of the nonlinear vehicle model (LTV MPC). We present a sufficient stability conditions for such LTV MPC scheme. The condition is derived for a general class of nonlinear discrete time systems and results into an additional convex constraint to be included in the LTV MPC design. For the AFS control problem, we compare the proposed LTV MPC scheme against the LTV MPC scheme in [6] where stability has been enforced with an ad-hoc constraint. Simulation and experimental tests up to 21 m/s on icy roads show the effectiveness of the LTV MPC formulation.

Abstract: While changing the handling characteristics of a conventional vehicle normally requires physical modification, a vehicle equipped with steer-by-wire can accomplish the same effect through active steering intervention. This paper presents an intuitive method for altering a vehicle's handling characteristics by augmenting the driver's steering command with full vehicle state feedback. The vehicle can be made more or less responsive depending on the driver's preference and particular operating conditions. Achieving a smooth, continuous change in handling quality requires both accurate state estimation and well-controlled steering inputs from the steer-by-wire system. Accurate estimates of vehicle states are available from a combination of global positioning system (GPS) and inertial navigation system (INS) sensor measurements. By canceling the effects of steering system dynamics and tire disturbance forces, the steer-by-wire system is able to track commanded steer angle with minimal error. Experimental results verify that with precise steering control and accurate state information, the handling modification is exactly equivalent to changing the front tire cornering stiffness.

Abstract: In this work a dynamic control allocation approach is presented for an automotive vehicle yaw stabilization scheme. The stabilization strategy consists of a high level module that deals with the vehicle motion control objective (yaw rate reference generation and tracking), a low level module that handles the braking control for each wheel (longitudinal slip control and maximal tire-road friction parameter estimation), and an intermediate level dynamic control allocation module that generates the longitudinal slip reference for the low level brake control module and commands front wheel steering angle corrections. The control allocation design is such that the actual torque about the yaw axis tends to the desired torque calculated form the high level module, with desirable distribution of control forces satisfying actuator constraints and minimal control effort objectives. Conditions for uniform asymptotic stability are given for the case when the control allocation includes adaptation of the tire-road maximal friction coefficients, and the scheme has been implemented in a realistic non linear multi body vehicle simulation environment. The simulation cases show that the yaw control allocation strategy stabilizes the vehicle in extreme maneuvers where the non linear vehicle yaw dynamics otherwise (without active braking or active steering) becomes unstable in the sense of over- or under steering. The control allocation implementation is efficient and suitable for low cost automotive electronic control units.