A Preview Steering Control Strategy Based on Computer Vision for Automated Vehicle Highway Systems

1993 ◽  
Vol 26 (2) ◽  
pp. 123-126 ◽  
Author(s):  
T. Inoue ◽  
K. Aoki ◽  
T. Suzuki ◽  
T. Yokoyama
Keyword(s):  
Computer Vision ◽  
Control Strategy ◽  
Steering Control ◽  
Automated Vehicle

scholarly journals Steering Control Method for an Underactuated Unicycle Robot Based on Dynamic Model

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Hongzhe Jin ◽  
Yang Zhang ◽  
Hui Zhang ◽  
Zhangxing Liu ◽  
Yubin Liu ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Control Strategy ◽  
Pitch Angle ◽  
Control Method ◽  
Steering Control ◽  
Dynamics Model ◽  
Gyroscope System ◽  
Simulation Results ◽  
Balance Structure ◽  
Gyroscope Precession

This paper proposes a lateral balancing structure based on precession effect of double-gyroscopes and its associated control strategy of the steering for an underactuated unicycle robot. Double-gyroscopes are symmetrically designed on the top of the unicycle robot and utilized to adjust the lateral balance of system. Such design can inhibit the disturbance of the gyroscope system to the pitch angle and is beneficial to maintain the lateral balance in the case of large roll angle fluctuations. Based on the analysis of the dynamics model, the gyroscope precession effects will be caused by the angular velocity of the bottom wheel and the roll angular velocity, i.e., resulting in a torque in the direction of the yaw. Then, a rapid response control strategy is proposed to use the torque to control the steering. Simulation results demonstrate the rationality of the lateral balance structure and the feasibility of the steering control method.

The Improved Algorithm to Preview Follower Control Applied Research on Intelligent Electric Vehicle

2014 ◽  
Vol 1079-1080 ◽  
pp. 1022-1025
Author(s):  
Sheng Rui Liu
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Control Method ◽  
Search Algorithm ◽  
Path Model ◽  
Driver Model ◽  
Domain Modeling ◽  
Steering Control ◽  
Tracking Accuracy ◽  
Electric Cars

This paper presents an improved preview follower, electric vehicle intelligent driver model of steering control strategy. And from the preview following the model proposed steering control method, and the preview follower algorithm, propose a new preview search algorithm, in order to ensure the preview points fall within the expected path, avoid the path curvature caused by excessive electric cars from the path. In addition, by considering the steady state response, to improve the precision of steering control strategy. Use of the multi domain modeling software Dipolar, combined with the electric vehicle dynamic model, the path model of the steering control strategy simulation. The simulation results show that the strategy is applied to electric vehicle path goal good tracking accuracy.

Vehicle Active Rear Wheel Steering Control Based on a Variable Transmission Ratio Control Strategy

2014 ◽  
Vol 709 ◽  
pp. 267-271 ◽  
Author(s):  
Yun Sheng Tan ◽  
Huan Shen ◽  
Man Hong Huang ◽  
Si Ran Zhang
Keyword(s):  
Control Strategy ◽  
Sliding Mode ◽  
Rear Wheel ◽  
Transmission Ratio ◽  
Steering Control ◽  
Yaw Rate ◽  
Human Driver ◽  
Variable Transmission ◽  
Mode Technique ◽  
The Ideal

In order to obtain the ideal steering performance, an active rear wheel steering (ARS) controller, based on the variable transmission ratio control strategy, is developed in this paper. ARS controller using sliding mode technique is designed to follow the desired yaw rate which is calculated by the ideal variable transmission ratio. Simulation result shows that, the proposed control strategy both obtains desired steering performance and provides the obvious benefits for the human driver.

Vehicle Dynamics Control Based on Linear Quadratic Regulator

2009 ◽  
Vol 16-19 ◽  
pp. 876-880
Author(s):  
Si Qi Zhang ◽  
Tian Xia Zhang ◽  
Shu Wen Zhou
Keyword(s):  
Control Strategy ◽  
Vehicle Dynamics ◽  
Linear Quadratic Regulator ◽  
Active Safety ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Yaw Rate ◽  
Vehicle Dynamics Control ◽  
Yaw Moment

The paper presents a vehicle dynamics control strategy devoted to prevent vehicles from spinning and drifting out. With vehicle dynamics control system, counter braking are applied at individual wheels as needed to generate an additional yaw moment until steering control and vehicle stability were regained. The Linear Quadratic Regulator (LQR) theory was designed to produce demanded yaw moment according to the error between the measured yaw rate and desired yaw rate. The results indicate the proposed system can significantly improve vehicle stability for active safety.

A New Control Strategy to Reduce Steering Torque Without Perceptible Vibration for Vehicles Equipped With Electric Power Steering

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
Masahiko Kurishige ◽  
Osamu Nishihara ◽  
Hiromitsu Kumamoto
Keyword(s):  
Angular Velocity ◽  
Electric Power ◽  
Control Strategy ◽  
Steering Wheel ◽  
Velocity Control ◽  
Steering Control ◽  
Electric Power Steering ◽  
Power Steering ◽  
Wide Range ◽  
Steering Torque

This paper proposes a new electric power steering control strategy, which significantly reduces the effort needed to change the steering direction of stationary vehicles. Previous attempts to reduce undesirable steering vibration have failed to reduce the steering torque because high-assist gains tend to produce oscillation or increase noise sensitivity. Herein, to eliminate this vibration, a new control strategy was developed based on pinion angular velocity control using a newly developed observer based on a simplified steering model. Tests yielded excellent estimations of the pinion angular velocity, and this made it possible to eliminate vibration at all steering wheel rotation speeds. Experiments with a test vehicle confirmed significant steering torque reduction, over a wide range of steering wheel speeds, without vibration transmission to the driver. The proposed control strategy allowed use of an assist gain more than three times higher than is conventional. Additionally, the proposed control strategy does not require supplemental sensors.

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