scholarly journals Path tracking control for autonomous vehicles with saturated input: A fuzzy fixed‐time learning control approach

2022 ◽  
Author(s):  
Xinrong Zhang ◽  
Ying Wang ◽  
Zeyu Yang ◽  
Jin Huang ◽  
Yanzhao Su
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Learning Control ◽  
Fixed Time ◽  
Path Tracking ◽  
Control Approach

A novel adaptive control approach for path tracking control of autonomous vehicles subject to uncertain dynamics

2020 ◽  
Vol 234 (8) ◽  
pp. 2115-2126
Author(s):  
Ardashir Mohammadzadeh ◽  
Hamid Taghavifar
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Control Method ◽  
Path Tracking ◽  
Operating Conditions ◽  
Ground Vehicles ◽  
Control Approach ◽  
Autonomous Ground Vehicles ◽  
Lane Changes ◽  
Uncertain Dynamics

Autonomous ground vehicles are constantly exposed to matched/mismatched uncertainties and disturbances and different operating conditions. Consequently, robustness to resist the undesirable effect of changes in the nominal parameters of the vehicle is a significant provision for satisfactory path-tracking control of these vehicles. The accomplishment of lateral path-tracking control is an essential task expectable from autonomous ground vehicles, particularly during critical maneuvers, abrupt cornering, and lane changes at high speeds. This paper presents a new control approach based on immersion and invariance control theorem. The asymptotic stability of the proposed method is ensured and the adaptation laws for the parameters are derived based on the I&I stability theorem. The effectiveness of the proposed control method is confirmed for autonomous ground vehicles systems while making a double-lane-change at various forward speeds. The robustness of the proposed control method is evaluated under parametric uncertainties related to the autonomous ground vehicle and different road conditions. The obtained results suggest that the proposed control method holds the capacity to be applied effectively to the path-tracking task of autonomous ground vehicles under a broad range of operating conditions, parametric uncertainness, and external disturbances.

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

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Runqiao Liu ◽  
Minxiang Wei ◽  
Nan Sang ◽  
Jianwei Wei
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Spline Interpolation ◽  
Lateral Displacement ◽  
Autonomous Vehicle ◽  
State Parameter ◽  
Front Wheel ◽  
Path Tracking ◽  
Adhesion Coefficient ◽  
Polar Coordinate

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.

scholarly journals MME-EKF-Based Path-Tracking Control of Autonomous Vehicles Considering Input Saturation

2019 ◽  
Vol 68 (6) ◽  
pp. 5246-5259 ◽  
Author(s):  
Chuan Hu ◽  
Zhenfeng Wang ◽  
Hamid Taghavifar ◽  
Jing Na ◽  
Yechen Qin ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Input Saturation ◽  
Path Tracking

scholarly journals Robust Path Tracking Control for Autonomous Vehicle Based on a Novel Fault Tolerant Adaptive Model Predictive Control Algorithm

2020 ◽  
Vol 10 (18) ◽  
pp. 6249
Author(s):  
Keke Geng ◽  
Shuaipeng Liu
Keyword(s):  
Predictive Control ◽  
Autonomous Vehicles ◽  
Tracking Control ◽  
Control Algorithm ◽  
Fault Tolerant ◽  
Path Tracking ◽  
Adaptive Model ◽  
Chi Square ◽  
Model Predictive Control Algorithm ◽  
Adaptive Model Predictive Control

Autonomous vehicles are expected to completely change the development model of the transportation industry and bring great convenience to our lives. Autonomous vehicles need to constantly obtain the motion status information with on-board sensors in order to formulate reasonable motion control strategies. Therefore, abnormal sensor readings or vehicle sensor failures can cause devastating consequences and can lead to fatal vehicle accidents. Hence, research on the fault tolerant control method is critical for autonomous vehicles. In this paper, we develop a robust fault tolerant path tracking control algorithm through combining the adaptive model predictive control algorithm for lateral path tracking control, improved weight assignment method for multi-sensor data fusion and fault isolation, and novel federal Kalman filtering approach with two states chi-square detector and residual chi-square detector for detection and identification of sensor fault in autonomous vehicles. Our numerical simulation and experiment demonstrate that the developed approach can detect fault signals and identify their sources with high accuracy and sensitivity. In the double line change path tracking control experiment, when the sensors failure occurs, the proposed method shows better robustness and effectiveness than the traditional methods. It is foreseeable that this research will contribute to the development of safer and more intelligent autonomous driving system, which in turn will promote the industrial development of intelligent transportation system.

scholarly journals Robust cooperative path tracking control algorithm for multi-vessel

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668330
Author(s):  
Jianfang Jiao ◽  
Guang Wang
Keyword(s):  
Control System ◽  
Tracking Control ◽  
Cooperative Control ◽  
Control Method ◽  
Path Tracking ◽  
Ocean Currents ◽  
Guidance System ◽  
Backstepping Method ◽  
Control Approach ◽  
Virtual Leader

The issue of distributed cooperative path tracking control for multi-vessel in the presence of ocean currents has addressed in this article. The proposed cooperative control approach is achieved by designing the guidance system and the control system. In order to achieve the multi-vessel’s coordination with the desired spatial formation, the guidance system is designed based on the strategy of virtual leader for supplying the desire path and relevant parameters for each vessel. In addition, a robust cooperative path tracking controller is designed to reject the disturbance of unknown ocean currents using the backstepping method and the adaptive control technology. The synchronization between all the vessels is achieved by defining same path parameter and same speed along the path through the guidance system. Global asymptotic stability is guaranteed by Lyapunov-based technique for the whole control system. The effectiveness of the proposed cooperative path tracking control method is demonstrated by numerical simulation.

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