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Journal articles on the topic 'Path tracking control'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

SZABOLCSI, Róbert. "MODEL PREDICTIVE CONTROL APPLIED IN UAV FLIGHT PATH TRACKING MISSIONS." Review of the Air Force Academy 17, no. 1 (2019): 49–62. http://dx.doi.org/10.19062/1842-9238.2019.17.1.7.

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2

Zhu, Liwei, Weiming Sun, Qian Zhang, En Lu, Jialin Xue, and Guohui Sha. "Tractor Path Tracking Control Method Based on Prescribed Performance and Sliding Mode Control." Agriculture 15, no. 15 (2025): 1663. https://doi.org/10.3390/agriculture15151663.

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In addressing the challenges of low path tracking accuracy and poor robustness during tractor autonomous operation, this paper proposes a path tracking control method for tractors that integrates prescribed performance with sliding mode control (SMC). A key feature of this control method is its inherent immunity to system parameter perturbations and external disturbances, while ensuring path tracking errors are constrained within a predefined range. First, the tractor is simplified into a two-wheeled vehicle model, and a path tracking error model is established based on the reference operation

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3

Yang, Zeyu, and Liang Hong. "Intelligent Vehicle Path Tracking Control Based on Model Predictive Control." Journal of Research in Science and Engineering 7, no. 3 (2025): 34–41. https://doi.org/10.53469/jrse.2024.07(03).8.

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With the rapid development of intelligent transportation system, the path tracking control of intelligent vehicles has become one of the key technologies. In this paper, the path tracking method of intelligent vehicles based on model predictive control (MPC) is studied deeply. Firstly, the control law for adaptive adjustment of the optimal time domain is designed based on the two-degree-of-freedom vehicle dynamics model and the model control algorithm. Next, the MPC trajectory tracking controller is built based on the error characteristics of the actual front wheel angle and the predicted fron

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Hu, Chaofang, Lingxue Zhao, Lei Cao, Patrick Tjan, and Na Wang. "Steering control based on model predictive control for obstacle avoidance of unmanned ground vehicle." Measurement and Control 53, no. 3-4 (2020): 501–18. http://dx.doi.org/10.1177/0020294019878871.

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In this paper, a strategy based on model predictive control consisting of path planning and path tracking is designed for obstacle avoidance steering control problem of the unmanned ground vehicle. The path planning controller can reconfigure a new obstacle avoidance reference path, where the constraint of the front-wheel-steering angle is transformed to formulate lateral acceleration constraint. The path tracking controller is designed to realize the accurate and fast following of the reconfigured path, and the control variable of tracking controller is steering angle. In this work, obstacles

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5

Najson, Federico, and Eliezer Kreindler. "Robot robust path tracking." Dynamics and Control 6, no. 4 (1996): 333–59. http://dx.doi.org/10.1007/bf02169812.

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Cong, GENG, ZHANG Jian, and LIU Jinxiong. "Path Tracking Control Based on Adaptive Control Period." IFAC-PapersOnLine 53, no. 5 (2020): 592–97. http://dx.doi.org/10.1016/j.ifacol.2021.04.148.

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Lee, Jaepoong, and Seongjin Yim. "Comparative Study of Path Tracking Controllers on Low Friction Roads for Autonomous Vehicles." Machines 11, no. 3 (2023): 403. http://dx.doi.org/10.3390/machines11030403.

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This paper presents a comparison among path tracking controllers on low-friction roads for autonomous vehicles. There are two goals in this paper. The first is to check the performance of path tracking controllers on low-friction roads, and the second is to check the effectiveness of four-wheel steering (4WS) for path tracking. To fully investigate the performance of path-tracking controllers on low-friction roads in this paper, the pure pursuit method, Stanley method, PID control, linear quadratic regulator, sliding mode control and model predictive control are designed and compared in terms

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Tan, Y. G., D. K. Liu, F. Liu, and Z. D. Zhou. "Digital robust preview control of path tracking." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 219, no. 1 (2005): 111–16. http://dx.doi.org/10.1243/095440705x9434.

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A robust optimal preview control method is presented in this paper for path tracking control problems to improve robustness and tracking precision of path tracking control systems. The known path information is used as reference input signals. Simulation results show that this method is valid not only for improving the performance of highly accurate trajectory control but also for improving system stabilization.

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9

Li, Yibo, Qi Cao, and Fang Liu. "Design of control system for driverless tractor." MATEC Web of Conferences 309 (2020): 04001. http://dx.doi.org/10.1051/matecconf/202030904001.

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This paper uses Tianjin TieNiu crawler tractor as the experimental platform to design an unmanned agricultural machinery control system based on RTK-GPS (Differential GPS Technology). The article expounds the overall design of the control system and proposes a path tracking control algorithm. Simulation and experimental results show that the control algorithm can complete the path tracking requirements of unmanned agricultural machinery. The system can control the unmanned agricultural machinery to follow a predetermined route. The speed is 0.55m/s, the maximum error of linear path tracking of

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10

Wang, Huiran, Qidong Wang, Wuwei Chen, Linfeng Zhao, and Dongkui Tan. "Path tracking based on model predictive control with variable predictive horizon." Transactions of the Institute of Measurement and Control 43, no. 12 (2021): 2676–88. http://dx.doi.org/10.1177/01423312211003809.

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Model predictive control is one of the main methods used in path tracking for autonomous vehicles. To improve the path tracking performance of the vehicle, a path tracking method based on model predictive control with variable predictive horizon is proposed in this paper. Based on the designed model predictive controller for path tracking, the response analysis of path tracking control system under the different predictive horizons is carried out to clarify the influence of predictive horizon on path tracking accuracy, driving comfort and real-time of the control algorithm. Then, taking the la

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11

Wen, Haojun, Xiaodong Ma, Chenjian Qin, Hao Chen, and Huanyu Kang. "Research on Path Tracking of Unmanned Spray Based on Dual Control Strategy." Agriculture 14, no. 4 (2024): 562. http://dx.doi.org/10.3390/agriculture14040562.

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The high clearance spray is a type of large and efficient agricultural machinery used for plant protection, and path tracking control is the key to ensure the efficient and safe operation of spray. Sliding mode control and other methods are commonly used abroad to track vehicles, while fuzzy control, neural networks and other methods are commonly used at home. However, domestic and foreign research on autonomous agricultural machinery is mainly focused on tractors and other machinery, while research on self-propelled spray in high clearance is less abundant. This paper takes the path tracking

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Wang, Quanyu, Jin He, Caiyun Lu, et al. "Modelling and Control Methods in Path Tracking Control for Autonomous Agricultural Vehicles: A Review of State of the Art and Challenges." Applied Sciences 13, no. 12 (2023): 7155. http://dx.doi.org/10.3390/app13127155.

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This paper provides a review of path-tracking strategies used in autonomous agricultural vehicles, mainly from two aspects: vehicle model construction and the development and improvement of path-tracking algorithms. Vehicle models are grouped into numerous types based on the structural characteristics and working conditions, including wheeled tractors, tracked tractors, rice transplanters, high clearance sprays, agricultural robots, agricultural tractor–trailers, etc. The application and improvement of path-tracking control methods are summarized based on the different working scenes and types

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Hu, Chaofang, and Lingxue Zhao. "Overtaking control strategy based on model predictive control with varying horizon for unmanned ground vehicle." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 235, no. 1 (2020): 78–92. http://dx.doi.org/10.1177/0954407020947515.

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In this paper, a synthesized novel strategy of varying predictive horizon-based model predictive control is proposed for the overtaking control of unmanned ground vehicle. The whole control strategy includes path planning and path tracking. First, the preferred path in presence of diverse constraints of states, inputs, and collision avoidance can be calculated using Gauss pseudospectral method where expected position, velocity, and attitude are provided. Correspondingly, the continuous optimal control problem is converted to discrete nonlinear programming. Second, model predictive control is d

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14

Zhang, Chengliang, Guanlei Gao, Chunzhao Zhao, Lei Li, Changpu Li, and Xiyuan Chen. "Research on 4WS Agricultural Machine Path Tracking Algorithm Based on Fuzzy Control Pure Tracking Model." Machines 10, no. 7 (2022): 597. http://dx.doi.org/10.3390/machines10070597.

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This paper presents a path tracking algorithm based on a fuzzy control pure tracking model for autonomous navigation of 4WS agricultural machines. The aim of this research is to implement path tracking for unmanned 4WS agricultural machinery and to solve the problem of difficult determination of forward-looking distances in pure tracking algorithms. By using the pure tracking algorithm model and a fuzzy controller, this paper converts the heading deviation and lateral deviation in one control cycle into the sum of lateral deviation as the first input to the fuzzy controller and the vehicle tra

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Deng, Zhaoxue, Yangrui Zhang, and Shuen Zhao. "Distributed Intelligent Vehicle Path Tracking and Stability Cooperative Control." World Electric Vehicle Journal 15, no. 3 (2024): 89. http://dx.doi.org/10.3390/wevj15030089.

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To enhance the path tracking capability and driving stability of intelligent vehicles, a controller is designed that synergizes active front wheel steering (AFS) and direct yaw moment (DYC), specifically tailored for distributed-drive electric vehicles. To address the challenge of determining the weight matrix in the linear quadratic regulator (LQR) algorithm during the path tracking design for intelligent vehicles on conventional roads, a genetic algorithm (GA)-optimized LQR path tracking controller is introduced. The 2-degree-of-freedom vehicle dynamics error model and the desired path infor

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Do, Khac Duc. "Path-tracking control of underactuated ships under tracking error constraints." Journal of Marine Science and Application 14, no. 4 (2015): 343–54. http://dx.doi.org/10.1007/s11804-015-1329-3.

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17

Liu, Yingjie, Yongli Sun, and Dawei Cui. "Optimum Path Tracking Control for the Inverse Problem of Vehicle Handling Dynamics Based on the hp-Adaptive Gaussian Pseudospectral Method." Mathematical Problems in Engineering 2021 (May 20, 2021): 1–15. http://dx.doi.org/10.1155/2021/6631049.

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We propose a vehicle path-tracking method based on the hp-adaptive Gaussian pseudospectral method (GPM), which tackles the problem of the slow convergence speed of the optimal control of vehicle path tracking. First, we establish a kinematic vehicle model by considering the path constraints and boundary constraints during the process of tracking the described path of a vehicle. Subsequently, finding the minimum error of the lateral distance between the prescribed path and the expected trajectory is set as the performance objective function. Finally, the vehicle path tracking problem is transfo

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18

Jeong, Yonghwan, and Seongjin Yim. "Integrated Path Tracking and Lateral Stability Control with Four-Wheel Independent Steering for Autonomous Electric Vehicles on Low Friction Roads." Machines 10, no. 8 (2022): 650. http://dx.doi.org/10.3390/machines10080650.

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This paper presents a method to design an integrated path tracking and lateral stability controller for an autonomous electric vehicle with four-wheel independent steering (4WIS) on low friction roads. Recent advances in autonomous driving have led to extensive studies on path tracking control. However, path tracking is difficult on low friction roads. In this paper, path tracking control was converted to the yaw rate tracking one to cope with problems caused by low friction roads. To generate a reference yaw rate for path tracking, we present several methods using a driver model and a target

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19

Zhang, Bingzhan, Zhiyuan Li, Yaoyao Ni, and Yujie Li. "Research on Path Planning and Tracking Control of Automatic Parking System." World Electric Vehicle Journal 13, no. 1 (2022): 14. http://dx.doi.org/10.3390/wevj13010014.

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In this paper, we focus on the parking path planning and path tracking control under parallel parking conditions with automatic parking system as the research object. In order to solve the problem of discontinuity of curvature in the path planning of traditional arc-straight combined curve, a quintic polynomial is used to smooth the path. we design a path tracking controller based on the incremental model predictive control (MPC). The preview control based on pure tracking algorithm is used as the comparison algorithm for path tracking. The feasibility of the controller is verified by building

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20

Klauer, Christian, Manuel Schwabe, and Hamid Mobalegh. "Path Tracking Control for Urban Autonomous Driving." IFAC-PapersOnLine 53, no. 2 (2020): 15705–12. http://dx.doi.org/10.1016/j.ifacol.2020.12.2569.

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21

Liu, Yingjie, and Dawei Cui. "Optimal Control of Vehicle Path Tracking Problem." World Electric Vehicle Journal 15, no. 9 (2024): 429. http://dx.doi.org/10.3390/wevj15090429.

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In response to the problem of low optimization efficiency and low tracking accuracy in vehicle path tracking, a comprehensive optimization method is established based on the 3-DOF vehicle motion model. The outer layer adopts the adaptive particle swarm optimization (APSO) method for parameter optimization, and improves the adaptive inertia weight and adaptive particle exploration rate to improve the convergence efficiency and global search ability of the population. The inner layer adopts the segmented Gaussian pseudospectral method (GPM) to optimize the vehicle motion trajectory, and sets con

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22

Patarinski, S., H. Van Brussel, and H. Thielemans. "Path Tracking Control of Wheeled Mobile Robots." IFAC Proceedings Volumes 26, no. 2 (1993): 893–96. http://dx.doi.org/10.1016/s1474-6670(17)48862-8.

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23

Salehpour, Saman, Yaghoub Pourasad, and Seyyed Hadi Taheri. "Vehicle path tracking by integrated chassis control." Journal of Central South University 22, no. 4 (2015): 1378–88. http://dx.doi.org/10.1007/s11771-015-2655-y.

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24

Edelmann, Johannes, Martin Haudum, and Manfred Plöchl. "Bicycle Rider Control Modelling for Path Tracking." IFAC-PapersOnLine 48, no. 1 (2015): 55–60. http://dx.doi.org/10.1016/j.ifacol.2015.05.070.

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25

Zhang, Bing, Changfu Zong, Guoying Chen, and Guiyuan Li. "An adaptive-prediction-horizon model prediction control for path tracking in a four-wheel independent control electric vehicle." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 12 (2019): 3246–62. http://dx.doi.org/10.1177/0954407018821527.

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An adaptive-prediction-horizon model prediction control-based path tracking controller for a four-wheel independent control electric vehicle is designed. Unlike traditional model prediction control with fixed prediction horizon, this paper devotes to satisfy the varied path tracking demand by adjusting online the prediction horizon of model prediction control according to its effect on vehicle dynamic characteristics. Vehicle dynamic stability quantized with the vehicle sideslip-feature phase plane is preferentially considered in the prediction horizon adjustment. For stability during switchin

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Lin, Fen, Shaobo Wang, Youqun Zhao, and Yizhang Cai. "Research on autonomous vehicle path tracking control considering roll stability." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 235, no. 1 (2020): 199–210. http://dx.doi.org/10.1177/0954407020942006.

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For autonomous vehicle path tracking control, the general path tracking controllers usually only consider vehicle dynamics’ constraints, without taking vehicle stability evaluation index into account. In this paper, a linear three-degree-of-freedom vehicle dynamics model is used as a predictive model. A comprehensive control method combining Model Predictive Control and Fuzzy proportional–integral–derivative control is proposed. Model Predictive Control is used to control the vehicle yaw stability and track the target path by considering the front wheel angle, sideslip angle, tire slip angles,

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Zhong, Shengzhi, Dengzhi Peng, Bin Huang, and Liutao Ma. "Path-Tracking Ability of the ASV on Different Adhesion Coefficient Roads Based on Slide Mode Control." Electronics 13, no. 1 (2023): 105. http://dx.doi.org/10.3390/electronics13010105.

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A vehicle equipped with an articulated steering system is often used in a particular area, such as a mine or the construction field. These sealing or semi-sealing fields make autonomous driving by an ASV (Articulated Steering Vehicle) easier than in passenger cars. Path-tracking is essential for an autonomous vehicle. To improve the path-tracking ability of an ASV, a path-tracking model is established based on dynamic theory. Then, the slide-mode predictive-control (SMPC) strategy is initiated to design the path-tracking controller. The improvement in the path-tracking ability on roads with di

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Miao, Baorui, and Chao Han. "Intelligent vehicle obstacle avoidance path-tracking control based on adaptive model predictive control." Mechanical Sciences 14, no. 1 (2023): 247–58. http://dx.doi.org/10.5194/ms-14-247-2023.

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Abstract. In order to solve the problems of low path-tracking accuracy, poor safety, and stability of intelligent vehicles with variable speeds and obstacles on the road, a double-layer adaptive model predictive controller (MPC) is designed. A vehicle point mass model is used in an obstacle avoidance planning controller, and the safety collision distance model is established according to the distance relationship between the vehicle and the obstacle to improve the driving safety of the vehicle. The design of the path-tracking controller is based on the three-degrees-of-freedom dynamics model.

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Cui, Peiling, Jingxian He, Jian Cui, and Haitao Li. "Improved Path Planning and Attitude Control Method for Agile Maneuver Satellite with Double-Gimbal Control Moment Gyros." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/878724.

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Double-gimbal control moment gyros can implement the satellite attitude maneuver efficiently. In order to reduce the energy consumption of double-gimbal control moment gyros and avoid the singularity state, an attitude maneuver path planning method is proposed by using the improved Fourier basis algorithm. Considering that the choice of the Fourier coefficients is important for the Fourier basis algorithm to converge quickly, a choosing method of the initial Fourier coefficients which can reduce the computational time of the path planning algorithm notably is proposed. Moreover, an attitude-tr

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Tian, Yantao, Kai Huang, Xuanhao Cao, Yulong Liu, and Xuewu Ji. "A hierarchical adaptive control framework of path tracking and roll stability for intelligent heavy vehicle with MPC." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 13 (2020): 2933–46. http://dx.doi.org/10.1177/0954407020923260.

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Roll stability is a major concern in the path tracking process of intelligent heavy vehicles in emergency steering maneuvers. Due to the coupling of lateral and roll motions of heavy vehicle, steering actions for path tracking may come into conflict with that for roll stability. In this paper, a hierarchical adaptive control framework composed of a supervisor, an upper controller and a lower controller is developed to mediate conflicting objectives of path tracking and roll stability via steering control. In the supervisor, path tracking control mode or cooperative control mode of path trackin

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31

Song, Chunyu, Xiaomin Guo, and Jianghua Sui. "Improved Model Predictive Control Algorithm for the Path Tracking Control of Ship Autonomous Berthing." Journal of Marine Science and Engineering 13, no. 7 (2025): 1273. https://doi.org/10.3390/jmse13071273.

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To address the issues of path tracking accuracy and control stability in autonomous ship berthing, an improved algorithm combining nonlinear model predictive control (NMPC) and convolutional neural networks (CNNs) is proposed in this paper. A CNN is employed to train on a large dataset of ship berthing trajectories, combined with the rolling optimization mechanism of NMPC. A high-precision path tracking control method is designed, which accounts for ship motion constraints and environmental disturbances. Simulation results show an 88.24% improvement in tracking precision over traditional MPC.

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Li, Zhihan, and Ying Nan. "Optimal Path Planning and Tracking Control Methods for Parafoil." Applied Sciences 13, no. 14 (2023): 8115. http://dx.doi.org/10.3390/app13148115.

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Due to the problems of flexible parafoil systems that are susceptible to complex disturbances, such as external wind fields and being difficult to control, it is necessary to study the path planning and tracking control methods of parafoil under complex conditions. In this paper, the particle model and dynamic model of the parafoil system are established, and the path planning method based on the original natural (ON) principle coupled with meteorological interference, terrain avoidance, and other environmental models is studied. Sliding mode control is introduced into the path tracking contro

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Zhang, Bingli, Jin Cheng, Pingping Zheng, Aojia Li, and Xiaoyu Cheng. "Research and Experiment on Path-Tracking Control of Autonomous Tractor Based on Lateral Deviation and Yaw Rate Feedback." Applied Engineering in Agriculture 37, no. 5 (2021): 891–99. http://dx.doi.org/10.13031/aea.14538.

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HighlightsAutomatic navigation technology in autonomous tractors is one of the key technologies in precision agriculture.A path-tracking control algorithm based on lateral deviation and yaw rate feedback is proposed.The modified steering angle was obtained by comparing the ideal yaw rate with the actual yaw rate.The results demonstrate the efficiency and superior accuracy of the proposed algorithm for tractor path-tracking control.Abstract. The performance of path-tracking control systems for autonomous tractors affects the quality and efficiency of farmland operations. The objective of this s

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Sharp, R. S. "Optimal stabilization and path-following controls for a bicycle." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 221, no. 4 (2007): 415–27. http://dx.doi.org/10.1243/0954406jmes529.

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The article is about stabilizing and path-tracking control of a bicycle by a rider. It is based on previously published work, in which it has been shown how a driver's or rider's preview of the roadway can be combined with the linear dynamics of an appropriate vehicle to yield a problem of discrete-time optimal-linear-control-theory form. In the previous work, it was shown how an optimal ‘driver’ converts path preview sample values, modelled as deriving from a Gaussian white-noise process, into steering control inputs to cause the vehicle to follow the previewed path. The control compromises b

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Wu, Bingshuai, Yingjie Liu, and Qianqian Wang. "Path Tracking of Autonomous Vehicle Based on Optimal Control." World Electric Vehicle Journal 16, no. 7 (2025): 340. https://doi.org/10.3390/wevj16070340.

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Path tracking control is a key technology in the research of intelligent vehicles. In the path tracking process of intelligent vehicles, there are multiple constraints and time-varying nonlinear system states. To address the problems of low tracking accuracy and poor robustness, a method based on Radau pseudospectral method(RPM) is designed. Firstly, a 4-DOF vehicle model was established. Secondly, the multiple phase Radau pseudospectral method(MPRPM) was used to discretize the control and state variables. Then, the path tracking problem was transformed into a nonlinear programming problem. Fi

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Li, Chenxu, Haobin Jiang, Shidian Ma, Shaokang Jiang, and Yue Li. "Automatic Parking Path Planning and Tracking Control Research for Intelligent Vehicles." Applied Sciences 10, no. 24 (2020): 9100. http://dx.doi.org/10.3390/app10249100.

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As a key technology for intelligent vehicles, automatic parking is becoming increasingly popular in the area of research. Automatic parking technology is available for safe and quick parking operations without a driver, and improving the driving comfort while greatly reducing the probability of parking accidents. An automatic parking path planning and tracking control method is proposed in this paper to resolve the following issues presented in the existing automatic parking systems, that is, low degree of automation in vehicle control; lack of conformity between segmented path planning and re

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Gao, Jianping, Wenjian Chai, and Yanfeng Wu. "Research on parallel parking path planning and tracking control of unmanned vehicles." Journal of Algorithms & Computational Technology 17 (January 2023): 174830262311649. http://dx.doi.org/10.1177/17483026231164932.

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Aiming at the problems of discontinuous curvature of the planned path, difficulty in finding the optimal reference path and high control accuracy requirements in tracking control for unmanned vehicles in the process of parallel parking, an optimal reference path planning method based on arc line and multi-objective optimization function and a path tracking control strategy based on nonlinear model predictive control are proposed. Firstly, the upper and lower boundaries of the exercisable area are obtained by the tangent of the arc and the straight line, and the multi-objective optimization fun

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Park, Manbok, and Seongjin Yim. "Design of Static Output Feedback Integrated Path Tracking Controller for Autonomous Vehicles." Processes 13, no. 5 (2025): 1335. https://doi.org/10.3390/pr13051335.

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This paper presents a method for designing a static output feedback integrated path tracking controller for autonomous vehicles. For path tracking, state–space model-based control methods, such as linear quadratic regulator, H∞ control, sliding mode control, and model predictive control, have been selected as controller design methodologies. However, these methods adopt full-state feedback. Among the state variables, the lateral velocity, or the side-slip angle, is hard to measure in real vehicles. To cope with this problem, it is desirable to use a state estimator or static output feedback (S

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Qiu, Runqi, and Shangfeng Xin. "Research on lateral control of autonomous vehicle based on driver steering model." Journal of Physics: Conference Series 2206, no. 1 (2022): 012021. http://dx.doi.org/10.1088/1742-6596/2206/1/012021.

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Abstract Path tracking is an important issue in autonomous driving research. In this paper, based on the vehicle two-degree-of-freedom linear dynamics model for path tracking, the study of vehicle path tracking is carried out by applying model predictive control. A linear state space model of the vehicle is established based on the linear two-degree-of-freedom dynamics model, which provides the basis for the path tracking research. Based on the established state space model and the model predictive control method, the path tracking control algorithm is established using the preview point of dr

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Deo, Ankit, Ayush Gupta, Himanshu Khemani, and Rashmi Ranjan Das. "Path tracking mobile robot using steppers." E3S Web of Conferences 87 (2019): 01028. http://dx.doi.org/10.1051/e3sconf/20198701028.

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In control of mobile robots, precision plays a key role in path tracking. In this paper we have intended to use hybrid stepper motors for precise control of the two wheeled robot. A control algorithm was developed to control the robot along different trajectories. We have found that stepper motors are more accurate for path tracking than normal DC motors with wheel encoders and one can obtain the implicit coordinates of the robot in runtime more precisely. Getting the precise coordinates of the robot at runtime can be used in various SLAM and VSLAM techniques for more accurate 3D mapping of th

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Cui, Sheng Min, Chao Zhang, Jian Feng Wang, and Kun Zhang. "Research on Path Tracking Control for Vision Based Intelligent Vehicle." Applied Mechanics and Materials 63-64 (June 2011): 305–8. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.305.

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This paper proposes an optimal control method to achieve the path tracking mission for the vision based intelligent vehicle. After the access of road trajectory, path tracking task is achieved by the intelligent vehicle automatic steering devices. The angle deviation and lateral deviation relative to the target path can be controlled in the smaller range by state feedback optimal control. A car model contained road information is established for the achievement of intelligent vehicle path tracking and automatic steering. Some values of the variables needed for the control system are obtained b

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Zhang, Hong Ji, and Yuan Yuan Ge. "Parameter Self-Adjusting Path Tracking Algorithm of Mobile Robots." Applied Mechanics and Materials 418 (September 2013): 10–14. http://dx.doi.org/10.4028/www.scientific.net/amm.418.10.

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For conventional fuzzy path tracking controller need to manually updated the control parameters in order to get better tracking control deficiencies and the lack of robustness of the problem when the control object is disturbed. Parameters self-adjusting tracking algorithm is proposed based on Cerebellum Model Articulation Controller(CMAC) and fuzzy logic composite of the control. The CAMC control logarithm first charged with tracking through learning objects charged with approximation of the object model, to learning cycle worth to control corresponding to the amount of correction correspondi

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Xu, Liyou, Jiaxing Hou, Xianghai Yan, Mengnan Liu, Junjiang Zhang, and Yuan Tao. "Research on Path Tracking of Intelligent Hybrid Articulated Tractor Based on Corrected Model Predictive Control." World Electric Vehicle Journal 16, no. 3 (2025): 161. https://doi.org/10.3390/wevj16030161.

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To improve the path tracking performance of intelligent hybrid articulated tractors in all working conditions in unmanned operation, a path-tracking control method based on corrected model predictive control is proposed. The kinematic model of the tractor is established by analyzing the tractor’s kinematics. Taking the lateral and longitudinal errors as the target and the speed and articulation angular acceleration as the constraints, a tracking control algorithm based on model predictive control is proposed. In addition, to improve the transient performance of the tractor in the path tracking

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44

Fan, Shengwen, Tao Xie, Zhigang Chen, Xuan Hu, and Lei Gao. "Optimal control of high speed unmanned vehicle path tracking." Journal of Physics: Conference Series 2195, no. 1 (2022): 012006. http://dx.doi.org/10.1088/1742-6596/2195/1/012006.

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Abstract In order to ensure the accuracy and stability of tracking control of driverless vehicle at high speed, an improved model predictive control method was designed. First of all, for the current high-speed unmanned vehicle tracking control field, there is little research and the tracking accuracy is poor. Starting from the three-degree-of-freedom vehicle dynamics model, by analyzing the vehicle yaw stability, the model is added with envelope constraints, and the linear time is derived. The variable path tracking controller model is designed with or without additional constraints. Through

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45

Lee, Jaepoong, and Seongjin Yim. "Path Tracking Control with Constraint on Tire Slip Angles under Low-Friction Road Conditions." Applied Sciences 14, no. 3 (2024): 1066. http://dx.doi.org/10.3390/app14031066.

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This paper presents a method to design a path tracking controller with a constraint on tire slip angles under low-friction road conditions. On a low-friction road surface, a lateral tire force is easily saturated and decreases as a tire slip angle increases by a large steering angle. Under this situation, a path tracking controller cannot achieve its maximum performance. To cope with this problem, it is necessary to limit tire slip angles to a value where the maximum lateral tire force is achieved. The most commonly used controllers for path tracking, linear quadratic regulator (LQR) and model

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46

Lei, Zhiyong, Xiaolong Ma, Xiwen Yuan, and Chuan He. "Research on Automatic Driving Path Tracking Control of Open-Pit Mine Transportation Vehicles with Delay Compensation." World Electric Vehicle Journal 13, no. 8 (2022): 134. http://dx.doi.org/10.3390/wevj13080134.

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The transportation environment of the open-pit mine is complex, the steering actuator of the mine vehicle has a large delay and poor response accuracy, and there are a lot of bumpy roads, large undulating ramps, and narrow-area curves in the mining area. These road sections seriously reduce the tracking accuracy of the mine vehicle path. Tracking control presents great challenges. Therefore, this study first conducts a simulation comparison study on commonly used path tracking methods such as pure pursuit control, Stanley control, and model predictive control (MPC), and then designs a path tra

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Kou, Farong, and Jie Ren. "MPC Path Tracking Control Based on GA-PAO." Highlights in Science, Engineering and Technology 122 (December 15, 2024): 97–103. https://doi.org/10.54097/9jszvh12.

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In order to improve the path tracking performance and stability of driverless vehicles. In this paper, a path tracking control strategy based on MPC is proposed to establish a three-degree-of-freedom vehicle dynamical model as a reference model, design the MPC controller, determine the objective function and add constraints. Optimization of important time-domain parameters of model predictive controllers by improved GA-PSO. A Carsim/Simulink co-simulation platform was built to simulate the controller under double-shifted line conditions to verify its effectiveness. Simulation results show that

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Xie, Yunfeng, Cong Li, Hui Jing, Weibiao An, and Junji Qin. "Integrated Control for Path Tracking and Stability Based on the Model Predictive Control for Four-Wheel Independently Driven Electric Vehicles." Machines 10, no. 10 (2022): 859. http://dx.doi.org/10.3390/machines10100859.

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Four-wheel independently driven electric vehicles are prone to rollover when driving at high speeds on high-adhesion roads and to sideslip on low-adhesion roads, increasing the risks associated with such vehicles. To solve this problem, this study proposes a path tracking and stability-integrated controller based on a model predictive control algorithm. First, a vehicle planar dynamics model and a roll dynamics model are established, and the lateral velocity, yaw rate, roll angle, and roll angle velocity of the vehicle are estimated based on an unscented Kalman filter. The lateral stiffness of

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Liu, Wenlong, Rui Guo, and Jingyi Zhao. "Adaptive Sliding Mode Predictive Control for Path Tracking of Wheeled Agricultural Vehicles." Machines 13, no. 2 (2025): 157. https://doi.org/10.3390/machines13020157.

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This study presents an adaptive sliding mode predictive control (ASMPC) algorithm intended to improve the control precision and robustness of path tracking for wheeled agricultural vehicles. Firstly, the kinematics state equations of the vehicle were established based on path tracking errors. Secondly, in order to design the path tracking controller by combining the precision advantage of model predictive control (MPC) algorithm with the robustness advantage of sliding mode control (SMC) algorithm, the sliding mode functions were designed and used as the output equations to establish the kinem

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Wu, Yiyang, Zhijiang Xie, and Ye Lu. "Steering Wheel AGV Path Tracking Control Based on Improved Pure Pursuit Model." Journal of Physics: Conference Series 2093, no. 1 (2021): 012005. http://dx.doi.org/10.1088/1742-6596/2093/1/012005.

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Abstract Aiming at the path tracking problem of the AGV transfer platform of an Optical module installing and calibrating system, this paper designs a pure pursuit control strategy in which the preview distance changes adaptively according to the current speed of AGV and the curvature of the reference path. Firstly, AGV kinematics model and pure pursuit model are established according to the geometric relationship. Then fitness function is established with tracking deviation and steering stability, and Particle swarm optimization (PSO) algorithm is used to optimize the preview distance of pure

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