Zhe Luo

A new vehicle path-following strategy of the steering driver model using general predictive control method

In order to build an accurate and effective model, simulation of driver behavior is absolutely essential for the development of advanced driver assistance systems and the current assessment of vehicle handling stability. The purpose of the proposed active steering control is to assist the driver to follow the desired path, especially in situations of the vehicle under strong external disturbance, distracted driver, or other unforeseen circumstances that can cause deviations. Based on the preview optimal simple artificial neural network driver model, an active steering system using general predictive control method is established. In order to improve the path-following capability of vehicles under disturbances, a general predictive controller, with the deviation between the vehicles’ actual and desired lateral positons as inputs and with the corrective steering wheel angle as outputs, is developed to follow the desired path. Meanwhile, adapting recursion least square method with the forgetting factor to estimate the parameters of the controlled auto-regressive and integrated moving average model of the vehicle is designed. The proposed vehicle path-following control system is evaluated in some typical conditions (e.g. under strong crosswind condition in standard double-lane-change, etc.). Simulation results and analysis have verified that this new vehicle path-following strategy, given by general predictive controller, is capable of capturing driver’s steering behavior and the amended driver steering angle can improve the dynamic performance of vehicle under some external disturbances.

Study of air-cushion system modelling for semi-track air-cushion vehicle body attitude control

To investigate the body attitude control for a semi-track air-cushion vehicle (STACV), a multi-air-cushions design scheme is adopted. Based on the experimental study of the developed single air-cushion (1-AC) STACV prototype along with its computational fluid dynamics (CFD) simulation, a two air-cushions (2-AC) configuration with controllable orifice valves is mainly examined for the pitch control of the STACV in this paper. Firstly, the relationships among the input air total pressure, the air-cushion forces, and air-cushion system related parameters are obtained according to the relevant testing and CFD simulations from the 1-AC system. Then, the relationships among the controllable orifice valve diameters, fan rotational speed and generated air-cushion pressures of the 2-AC system are acquired using CFD simulations. Finally, the forward and reverse air-cushion system models are established by neural network. This method can be used as a reference in future body attitude control of the STACV with more air-cushions.

Modeling and simulation of air-boots for a novel soft-terrain walking concept vehicle

It has been a difficult but hot subject to improve the vehicle trafficability in some complex soft-terrain environments in the research area for off-road vehicle dynamics and control. Based on previous study for a semi-tracked air-cushion vehicle, a novel soft-terrain concept vehicle with a walking mechanism by using six air-cushion boots is proposed. The vehicle motion is realized by driving-gears while the boots vertical motion is realized by air charging or discharging. Therefore the modeling of a single boot is the first important task for vehicle motion modeling and control. In this paper, the structure and working principle of the vehicle are described firstly. Then a parameterized steady-state model of air-boots considering the rubber elastic deformation is established, which is verified by comparing with finite element simulation results. The model can still be used while the size and material of boots changing. Finally, a numerical method to simulate boot air-charging process by using the established model is discussed, and a typical process is taken as an example. The research results provide useful references for future work on vehicle modeling and control algorithm design.