Optimal control approach developed to Four-Wheel Active Steering Vehicles

Amdouni, Imen; Jeddi, Nafaa; Amraoui, Lilia El

doi:10.1109/icmsao.2013.6552547

Cited by 11 publications

(4 citation statements)

References 8 publications

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“…Finally, the target paths can be converted into the desired front and rear wheel steering angles and used as initial inputs of autonomous vehicles. For a 4WS vehicle, the yaw rate response is generally set to a first-order lag response and the sideslip angle response is generally set to 0 [27][28][29][30][31]. Its initial inputs can be formulated as follows:…”

Section: Circular Bend and Vehicle Modelmentioning

confidence: 99%

Research on Curved Path Tracking Control for Four-Wheel Steering Vehicle considering Road Adhesion Coefficient

Liu

Wei

Sang

et al. 2020

Mathematical Problems in Engineering

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Curved path tracking control is one of the most important functions of autonomous vehicles. First, small turning radius circular bends considering bend quadrant and travel direction restrictions are planned by polar coordinate equations. Second, an estimator of a vehicle state parameter and road adhesion coefficient based on an extended Kalman filter is designed. To improve the convenience and accuracy of the estimator, the combined slip theory, trigonometric function group fitting, and cubic spline interpolation are used to estimate the longitudinal and lateral forces of the tire model (215/55 R17). Third, to minimize the lateral displacement and yaw angle tracking errors of a four-wheel steering (4WS) vehicle, the front-wheel steering angle of the 4WS vehicle is corrected by a model predictive control (MPC) feed-back controller. Finally, CarSim® simulation results show that the 4WS autonomous vehicle based on the MPC feed-back controller can not only significantly improve the curved path tracking performance but also effectively reduce the probability of drifting or rushing out of the runway at high speeds and on low-adhesion roads.

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Section: Circular Bend and Vehicle Modelmentioning

confidence: 99%

Research on Curved Path Tracking Control for Four-Wheel Steering Vehicle considering Road Adhesion Coefficient

Liu

Wei

Sang

et al. 2020

Mathematical Problems in Engineering

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show abstract

“…For a 4WS autonomous vehicle, the yaw rate response is generally set to a first-order lag response, and the sideslip angle response is generally set to 0. 27 Its transfer functions from the steering wheel angle to the front- and rear-wheel steering angles are expressed as follows…”

Section: Initial Inputs Of Autonomous Vehiclementioning

confidence: 99%

Emergency obstacle avoidance trajectory tracking control based on active disturbance rejection for autonomous vehicles

Liu

Wei

Sang

2020

International Journal of Advanced Robotic Systems

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To solve the problem of understeer and oversteer for autonomous vehicle under high-speed emergency obstacle avoidance conditions, considering the effect of steering angular frequency and vehicle speed on yaw rate for four-wheel steering vehicles in the frequency domain, a feed-forward controller for four-wheel steering autonomous vehicles that tracks the desired yaw rate is proposed. Furthermore, the steering sensitivity coefficient of the vehicle is compensated linearly with the change in the steering angular frequency and vehicle speed. In addition, to minimize the tracking errors caused by vehicle nonlinearity and external disturbances, an active disturbance rejection control feedback controller that tracks the desired lateral displacement and desired yaw angle is designed. Finally, CarSim® obstacle avoidance simulation results show that an autonomous vehicle with the four-wheel steering path tracking controller consisting of feed-forward control and feedback control could not only improve the tire lateral forces but also reduce tail flicking (oversteer) and pushing ahead (understeer) under high-speed emergency obstacle avoidance conditions.

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“…Zhao [19] studies the dynamic model and motion constraints of AGV and applies it to the navigation control process, while the precision of the trajectory tracking is difficult to guarantee. There are also numerous studies on developing controllers abroad to ensure the effectiveness of path trackings, such as optimal control [20], nonlinear decoupling control with observers [21], unknown disturbance observers [22] and multi-mode control strategy selector [23].…”

Section: Introductionmentioning

confidence: 99%

Path Tracking Controller Design of Automatic Guided Vehicle Based on Four-Wheeled Omnidirectional Motion Model

Yang

2020

IJAME

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This paper presents a new design of omnidirectional automatic guided vehicle based on a hub motor, and proposes a joint controller for path tracking. The proposed controller includes two parts: a fuzzy controller and a multi-step predictive optimal controller. Firstly, based on various steering conditions, the kinematics model of the whole vehicle and the pose (position, angle) model in the global coordinate system are introduced. Secondly, based on the modeling, the joint controller is designed. Lateral deviation and course deviation are used as the input variables of the control system, and the threshold value is switched according to the value of the input variable to realise the correction of the large range of posture deviation. Finally, the joint controller is implemented by using the industrial PC and the self-developed control system based on the Freescale minimum system. Path tracking experiments were made under the straight and circular paths to test the ability of the joint controller for reducing the pose deviation. The experimental results show that the designed guided vehicle has excellent ability to path tracking, which meets the design goals.

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Optimal control approach developed to Four-Wheel Active Steering Vehicles

Cited by 11 publications

References 8 publications

Research on Curved Path Tracking Control for Four-Wheel Steering Vehicle considering Road Adhesion Coefficient

Research on Curved Path Tracking Control for Four-Wheel Steering Vehicle considering Road Adhesion Coefficient

Emergency obstacle avoidance trajectory tracking control based on active disturbance rejection for autonomous vehicles

Path Tracking Controller Design of Automatic Guided Vehicle Based on Four-Wheeled Omnidirectional Motion Model

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