Vehicle Stability Improvement by Active Front Steering Control

2007 ◽  
Author(s):  
Deling Chen ◽  
Chengliang Yin ◽  
Li Chen
Keyword(s):  
Time Estimation ◽  
Linear Quadratic Regulator ◽  
Steering System ◽  
Angle Measurement ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Sideslip Angle ◽  
Feedback Parameter ◽  
Active Front Steering

This paper presents the vehicle stability improvement by active front steering (AFS) control. Firstly, a mathematical model of the steering system incorporating vehicle dynamics is analyzed based on the structure of the AFS system. Then feedback controller with linear quadratic regulator (LQR) optimization is proposed. In the controller, the assisted motor in the system is controlled by the combination of feedforward method and feedback method. And the feedback parameter is the yaw rate together with the sideslip angle. Due to the difficulties associated with the sideslip angle measurement of vehicle, a state observer is designed to provide real time estimation to meet the demands of feedback. In the last, the system is simulated in MATLAB. The results show that the vehicle handling stability is improved with the AFS control, and the effectiveness of the control system is demonstrated.

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.

Analysis of Synchronous Moment for Active Front Steering and a Two Actuated Wheels of Electric Vehicle Based on Dynamic Stability Enhancement

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Eid. S. Mohamed ◽  
Mh.I. Khalil ◽  
Ahmed A.A. Saad
Keyword(s):  
Linear Quadratic Regulator ◽  
Vehicle Stability ◽  
Linear Quadratic ◽  
Smart Systems ◽  
Active Front Steering ◽  
Lqr Controller ◽  
Optimal Linear ◽  
Vehicle Trajectory ◽  
Stability Enhancement ◽  
Yaw Moment

Active Front Steering (AFS) and Direct Yaw moment Controller (DYC) are the vehicle smart systems to improve the vehicle stability and safety. The AFS uses front wheels Steer-By-Wire (SBW) system. DYC uses Rear Independent in Wheel Actuated Electric Vehicles (RIWA-EVs). It generates yaw moment to correct the vehicle state deviations. The proposed controller algorithm consists of two levels. First level feedback controller evaluate the optimal yaw moment generated to achieve the desired vehicle trajectory motion with minimize the yaw rate and side-slip errors. The second level controller is utilized to allocate the required front steer angle and traction/ regeneration to the RIWA embedded in rear wheels by taking into account the tire slip. An optimal Linear Quadratic Regulator (LQR) controller is designed, and its controller effectiveness is evaluated under various input driving manoeuvres. The results indicate that the integrated AFS/DYC can significantly stabilize the vehicle motion and highly reduce the driver’s workload. The laboratory experiment of AFS subsystem, for adequate actual front steering angle is measured, in order to apply in vehicle model to predict the responses. The results disclose that the RMS can be an effective route to monitor the vehicle stability.

Active Command-Steering Control of Tractor and Three Full Trailers for Tractor-Track Following

2006 ◽  
Author(s):  
Krishna Rangavajhula ◽  
H.-S. Jacob Tsao
Keyword(s):  
High Speed ◽  
Control Strategies ◽  
Linear Quadratic Regulator ◽  
Cost Effective ◽  
Steering Control ◽  
Linear Quadratic ◽  
Amplification Ratio ◽  
High Speeds ◽  
Lqr Controller ◽  
Optimal Linear

A key source of safety and infrastructure issues for operations of longer combination vehicles (LCVs) is off-tracking, which has been used to refer to the general phenomenon that the rear wheels of a truck do not follow the track of the front wheels and wander off the travel lane. In this paper, we examine the effectiveness of command-steering in reducing off-tracking during a 90-degree turn at low and high speeds in an articulated system with a tractor and three full trailers. In command steering, rear front axles of the trailers are steered proportionately to the articulation angle between the tractor and trailing units. We then consider several control strategies to minimize off-tracking and rearward amplification of this system. A minimum rearward amplification ratio (RWA), as a surrogate for minimum off tracking, has been used as the control criterion for medium to high speeds to arrive at an optimal Linear Quadratic Regulator (LQR) controller. As for low speeds, the maximum radial offset between the tractor and trailer 3 is minimized in the design of the controller. Robustness of the optimal controller with respect to tyre-parameter perturbations is then examined. Based on the simulation results, we find that, active command steering is very effective in reducing off tracking at low- as well as high-speed 90-degree turns. To achieve acceptable levels of RWA and off tracking, at least two of the three trailers must be actively command-steered. Among the three two-trailer-steering possibilities, actively steering trailers 1 and 2 is most cost-effective and results in the lowest RWA for medium- to high- speeds (at which RWA is important), and off-tracking is practically eliminated for all speed regimes considered.

Design of an Optimal Control Strategy for an Active Front Steering System

2006 ◽  
Author(s):  
Avesta Goodarzi ◽  
Ebrahim Esmailzadeh ◽  
Babak Nadarkhani
Keyword(s):  
Optimal Control ◽  
Vehicle Dynamics ◽  
Steering System ◽  
Lateral Acceleration ◽  
Manufacturing Companies ◽  
Vehicle Dynamic ◽  
Steering Control ◽  
Optimal Control Strategy ◽  
Active Front Steering ◽  
Innovative System

The concept of active steering control (ASC) has been considered by several researchers as well as auto manufacturing companies during recent years. This innovative system permits any correction of the driver’s steering angle in order to achieve the desired vehicle dynamic behavior. An optimal control law to evaluate the steering angle’s correction of the front wheels, being part of an active front steering system (AFS), has been developed. For this purpose a specific lateral vehicle dynamics index is defined in which way that the minimization of the performance index lead to improved vehicle dynamics. The optimal values of the control law’s gains are determined analytically. The performance of the proposed control system has been verified using 8-DOF nonlinear vehicle dynamic model. The simulation results illustrate that considerable improvement in vehicle handling is achieved particularly for the cases of the low and mid-range lateral acceleration maneuvers.

A Mathematical Model of Driver Steering Control Including Neuromuscular Dynamics

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
Andrew J. Pick ◽  
David J. Cole
Keyword(s):  
Path Following ◽  
Linear Quadratic Regulator ◽  
Driver Model ◽  
Steering Wheel ◽  
Steering Control ◽  
Linear Quadratic ◽  
Reflex Action ◽  
Path Following Control ◽  
Steering Torque ◽  
Neuromuscular Dynamics

A mathematical driver model is introduced in order to explain the driver steering behavior observed during successive double lane-change maneuvers. The model consists of a linear quadratic regulator path-following controller coupled to a neuromuscular system (NMS). The NMS generates the steering wheel angle demanded by the path-following controller. The model demonstrates that reflex action and muscle cocontraction improve the steer angle control and thus increase the path-following accuracy. Muscle cocontraction does not have the destabilizing effect of reflex action, but there is an energy cost. A cost function is used to calculate optimum values of cocontraction that are similar to those observed in the experiments. The observed reduction in cocontraction with experience of the vehicle is explained by the driver learning to predict the steering torque feedback. The observed robustness of the path-following control to unexpected changes in steering torque feedback arises from the reflex action and cocontraction stiffness of the NMS. The findings contribute to the understanding of driver-vehicle dynamic interaction. Further work is planned to improve the model; the aim is to enable the optimum design of steering feedback early in the vehicle development process.

Fuzzy Logic Based Vehicle Stability Enhancement Through Combined Differential Braking and Active Front Steering

2005 ◽  
Author(s):  
J. Ahmadi ◽  
A. Ghaffari ◽  
R. Kazemi
Keyword(s):  
Fuzzy Logic ◽  
Steering System ◽  
Vehicle Stability ◽  
Fuzzy Logic Controllers ◽  
Vehicle Model ◽  
Active Front Steering ◽  
Highly Nonlinear ◽  
Road Condition ◽  
The Stability ◽  
Stability Enhancement

This paper examines the usefulness of a combined differential braking and active front steering system on the stability enhancement of a vehicle. The two manipulated inputs for steering intervention are the added front steer angle and the brake torque, where the later is applied at only one wheel at a time. In this study active front steering controller is designed independent of differential braking controller. Since the yaw and lateral motions are highly nonlinear, two fuzzy logic controllers are constructed to compensate the effects of road condition and parameter variation. Computer simulations using nonlinear seven degree of freedom vehicle model show the strong capability of the combined approach and its relative merit compared to the case that one subsystem is actuated.

Active camber system for lateral stability improvement of urban vehicles

2019 ◽  
Vol 233 (14) ◽  
pp. 3824-3838 ◽  
Author(s):  
Mansour Ataei ◽  
Chen Tang ◽  
Amir Khajepour ◽  
Soo Jeon
Keyword(s):  
Vehicle Dynamics ◽  
Vehicle Stability ◽  
Lateral Stability ◽  
Tire Model ◽  
Vehicle Model ◽  
Sideslip Angle ◽  
Friction Forces ◽  
Additional Degree ◽  
Tire Force ◽  
Active Front Steering

A suspension system with the capability of cambering has an additional degree of freedom for changing camber angle to increase the maximum lateral tire force. This study investigates the effects of cambering on overall vehicle stability with emphasis on applications to urban vehicles. A full vehicle model with a reliable tire model including camber effects is employed to investigate the vehicle dynamics behavior under cambering. Besides, a linearized vehicle model is used to analytically study the effects of camber lateral forces on vehicle dynamics. Vehicle behavior for different configurations of camber angles in front and rear wheels is studied and compared. Then, an active camber system is suggested for improvement of vehicle lateral stability. Specifically, performances of active front camber, active rear camber, and their combination are investigated. The results show that a proper strategy for camber control can improve both yaw rate and sideslip angle, simultaneously. Finally, the active front camber system is compared with the well-known active front steering. It is shown that, utilizing more friction forces at the limits, active front camber is more effective in improving maneuverability and lateral stability than active front steering.

scholarly journals Development of an Autonomous Two-Wheeled Vehicle Robot

2011 ◽  
Vol 2-3 ◽  
pp. 390-395
Author(s):  
Minoru Sasaki ◽  
Hidenobu Tanaka ◽  
Satoshi Ito
Keyword(s):  
Control Systems ◽  
Integral Method ◽  
Linear Quadratic Regulator ◽  
Steering Control ◽  
Linear Quadratic ◽  
Wheeled Vehicle ◽  
Roll Rate ◽  
Simulation Results ◽  
Quadratic Integral ◽  
Steering Torque

This paper describes a development of an autonomous two-wheeled vehicle robot. The model of the two-wheeled vehicle using steering control is derived. The control systems are designed by linear quadratic regulator and linear quadratic integral method. Stabilization is achieved by measuring roll angle and roll rate and controlling the steering torque. The experimental results and simulation results show stable running control of the two-wheeled vehicle robot and coincident with each other. The approach is validated through these results.

scholarly journals A New Adaptive System for Suppression of Transient Wind Disturbance in Large Antennas

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Wei Liang ◽  
Jin Huang ◽  
Jie Zhang
Keyword(s):  
Adaptive System ◽  
Surface Profile ◽  
Time Estimation ◽  
Linear Quadratic Regulator ◽  
Minimum Variance ◽  
Wind Disturbance ◽  
Linear Quadratic ◽  
Tension Distribution ◽  
Vibration State ◽  
Transient Wind

Under transient wind disturbance, vibration deformation of the large antenna surface profile causes deterioration of pointing performance. This paper presents a new adaptive system to suppress unknown transient wind disturbance. First, to monitor the vibration, based on the acceleration measurement and a low-order flexible model considering equivalent identification of forces, the real-time estimation of the vibration state is obtained in an unbiased minimum-variance way. Next, a novel four-cable-actuator mechanism with a circular slide track is proposed for suppressing the vibration, in which the locations of the cable drivers on the slide track are determined according to the attitude of the antenna, and the expected tension distribution of the cables is found by the vibration state and the optimal gain of the linear quadratic regulator (LQR). In the end, the simulation implementation of a 7.3 m antenna under the transient wind disturbance is used to verify the effectiveness of the proposed method.

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