Active steering control with front wheel steering

Author(s):  
Bing Zheng ◽  
P. Oh ◽  
B. Lenart
2019 ◽  
Vol 11 (11) ◽  
pp. 168781401989210 ◽  
Author(s):  
Guangfei Xu ◽  
Peisong Diao ◽  
Xiangkun He ◽  
Jian Wu ◽  
Guosong Wang ◽  
...  

In the research process of automotive active steering control, due to the model uncertainty, road surface interference, sensor noise, and other influences, the control accuracy of the active steering system will be reduced, and the driver’s road sense will become worse. The traditional robust controller can solve the model uncertainty, pavement disturbance and sensor noise in the design process, but cannot consider the performance enough. Therefore, this article proposes an active steering control method based on linear matrix inequality. In this method, the model uncertainty, road interference, sensor noise, yaw velocity, and slip side angle tracking errors are all considered as constraint targets, respectively, so that the performance and robust stability of the active front steering system can be guaranteed. Finally, simulation and hardware in the loop experiment are implemented to verify the effect of active front steering system under the linear matrix inequality controller. The results show that the proposed control method can achieve better robust performance and robust stability.


Author(s):  
Yoshiyuki Tanaka ◽  
Yusuke Kashiba ◽  
Naoki Yamada ◽  
Takamasa Suetomi ◽  
Kazuo Nishikawa ◽  
...  

Author(s):  
Shih-Ken Chen ◽  
William C. Lin ◽  
Yuen-Kwok Steve Chin ◽  
Xiaodi Kang

This paper presents an analysis and comparison of a vehicle with active front steering and rear-wheel steering. Based on linear analysis of base vehicle characteristics under varying speed and road surfaces, desirable vehicle response characteristics are presented and a set of performance matrices for active steering systems is formulated. Using pole-placement approach, controllability issues under active front wheel steering and rear- wheel steering controls are discussed. A frequency response optimization approach is then used to design the closed-loop controllers.


Author(s):  
Keji Chen ◽  
Xiaofei Pei ◽  
Daoyuan Sun ◽  
Zhenfu Chen ◽  
Xuexun Guo ◽  
...  

Leveraging the advancements in sensor and mapping technologies, the collision-free autonomous vehicle becomes possible in the future. In this article, a case study of collision avoidance by active steering control is presented and verified by a driver-in-the-loop platform. The proposed control system integrates a risk assessment algorithm and a hierarchical model predictive control approach to ensure a safe driving. First, a fuzzy logic is used to estimate the potential conflict. Besides, a nonlinear model predictive control is introduced in the upper layer of the model predictive controller to generate a collision-free trajectory. Furthermore, the lower layer determines the optimal steering angle based on the linear time-variant model predictive control to follow the replanning path. The performance of the controller has been evaluated in the real-time driver-in-the-loop test. The results show that the autonomous vehicle is able to avoid the collision with the surrounding vehicle that is operated by a real driver, and the performance of collision avoidance is improved by means of the risk assessment.


2019 ◽  
Vol 79 (4) ◽  
pp. 273
Author(s):  
Muhammad Arshad Khan ◽  
Muhammad Faisal Aftab ◽  
Ejaz Ahmad ◽  
Iljoong Youn

2012 ◽  
Vol 18 (5) ◽  
pp. 473-484 ◽  
Author(s):  
Riccardo Marino ◽  
Stefano Scalzi ◽  
Mariana Netto

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