两轮差速AGV的轨迹跟踪控制研究
Study on Trajectory Tracking Control of Two-Wheel Difference Speed of AGV
DOI: 10.12677/SEA.2017.64007, PDF, HTML, XML,  被引量 下载: 2,384  浏览: 7,816 
作者: 杨李朋, 张文丰, 王 昊：上海电力学院 能源与机械工程学院，上海
关键词: AGV；Back-stepping；轨迹跟踪；Lyapunov；AGV； Back-Stepping； Trajectory Tracking； Lyapunov
摘要: 本文针对AGV的轨迹跟踪控制问题，提出了一种Back-stepping的控制算法。首先，建立AGV的运动学模型和跟踪位姿误差模型；然后，利用Back-stepping方法将整个非线性系统进行分解成若干子系统，且对子系统分步构造Lyapunov函数和中间虚拟控制量，一直后退导出系统的控制律；最后，在MATLAB环境下分别进行了直线轨迹跟踪和圆轨迹跟踪的仿真实验，结果表明跟踪误差很快收敛于零，轨迹跟踪效果良好。Back-stepping方法结合Lyapunov理论设计的控制器，不仅能实现对AGV对参考轨迹全局渐进跟踪，还具有较高的精确性和鲁棒性。
Abstract: In view of trajectory tracking control problem of AGV, a Back-stepping control algorithm is pro-posed. Firstly, the AGV kinematics model and tracking pose error model are established; Then, the whole nonlinear system is decomposed into several sub-systems by using Back-stepping method, and the Lyapunov function and the intermediate virtual control are constructed and has been back to export control law of system step by step. Finally, the simulation experiment of line tracking and circular tracking was carried out in MATLAB environment. The results show that the tracking error converges to zero quickly, and trajectory tracking effect is wonderful. Back-stepping method combined with Lyapunov theory design the controller, not only can achieve AGV on the reference trajectory global asymptotic tracking, but also has high accuracy and robustness.
文章引用：杨李朋, 张文丰, 王昊. 两轮差速AGV的轨迹跟踪控制研究[J]. 软件工程与应用, 2017, 6(4): 59-67. https://doi.org/10.12677/SEA.2017.64007

参考文献

[1] Pratama, P.S. and Gulakari, A.V. (2016) Trajectory Tracking and Fault Detection Algorithm for Automatic Guided Vehicle Based on Multiple Positioning Modules. International Journal of Control, Automation and Systems, 14, 400- 410.
https://doi.org/10.1007/s12555-014-0294-y
[2] Pratama, P.S., Luan, B.T., et al. (2014) Trajectory Tracking Algorithm for Automatic Guided Vehicle Based on Adaptive Backstepping Control Method. Recent Advances in Electrical Engineering and Related Sciences, 11, 535-543.
https://doi.org/10.1007/978-3-642-41968-3_53
[3] 王海燕. 基于全局PID模糊滑模算法的机器人跟踪控制仿真[J]. 西南师范大学学报, 2015, 40(10): 57-63.
[4] Zhu, M. and Chen, H.Y. (2016) A Model Predictive Speed Tracking Control Approach for Autonomous Ground Vehicles. Mechanical Systems and Signal Processing, 12, 68-75.
[5] 康浩博, 王建辉. 基于安全性考虑的五自由度外骨骼式上肢康复机器人自适应控制[J]. 中国科技论文, 2014, 9(7): 844-851.
[6] Xin, L.J. and Wang, Q.L. (2016) Robust Adaptive Tracking Control of Wheeled Mobile Robot. Robotics and Autonomous Systems, 78, 36-48.
https://doi.org/10.1016/j.robot.2016.01.002
[7] 卢彬. 基于单片机的差速驱动导引小车运动控制[D]: [硕士学位论文]. 西安: 西安理工大学, 2010.
[8] Huang, H.-C. and Chiang, C.-H. (2016) An Evolutionary Radial Basis Function Neural Network with Robust Genetic-Based Immunecomputing for Online Tracking Control of Autonomous Robots. Neural Processing Letters, 44, 19- 35.
https://doi.org/10.1007/s11063-015-9452-3
[9] Yin, X.-H. and Zhao, H. (2013) On a New Sectionalized Motion Control Strategy for Automated Guided Vehicles: Modeling and Simulation Validation. Robotics, 69, 637-646.
https://doi.org/10.1007/s00170-013-5035-5
[10] 王仲民, 岳宏, 刘继岩. 轮式移动机器人轨迹跟踪控制[J]. 太原理工大学学报, 2005, 4(36): 474-476.
[11] Pratama, P.S., Jeong, J.H., et al. (2016) Adaptive Backstepping Control Design for Trajectory Tracking of Automatic Guided Vehicles. Lecture Notes in Electrical Engineering, 9, 589-602.
https://doi.org/10.1007/978-3-319-27247-4_50
[12] 吕学勤, 陈文君, 吴毅雄. 基于Back-Stepping 的机器人轨迹跟踪[J]. 机器人与自动化, 2013, 24(9): 56-61.
[13] Klančar, G., Matko, D. and Blažič, S. (2011) A Control Strategy for Platoons of Differential Drive Wheeled Mobile Robot. Robotics and Autonomous Systems, 59, 57-64.
https://doi.org/10.1016/j.robot.2010.12.002
[14] 吴剑, 黄晓娟, 江维. 基于Back-stepping 的轮式机器人轨迹跟踪[J]. 南昌航空大学学报, 2012, 4(26): 89-93.
[15] 李平, 王建锋, 李娜, 惠珂. 基于lyapunov直接法的移动机器人运动控制研究[J]. 中国科技论文, 2016, 2(11): 160-163.
[16] 叶锦华, 李迪, 叶峰. 不确定完整AGV的自适应反演滑模控制[J]. 华南理工大学学报, 2011, 39(12): 32-37.

为你推荐