广西师范大学学报(自然科学版) ›› 2023, Vol. 41 ›› Issue (2): 36-48.doi: 10.16088/j.issn.1001-6600.2022042004

• 研究论文 • 上一篇    下一篇

无模型坐标补偿积分滑模约束的自动驾驶汽车轨迹跟踪控制

卢许孟, 南新元*, 夏斯博   

  1. 新疆大学 电气工程学院,新疆 乌鲁木齐 830047
  • 收稿日期:2022-04-20 修回日期:2022-06-03 出版日期:2023-03-25 发布日期:2023-04-25
  • 通讯作者: 南新元(1967—),男,新疆乌鲁木齐人,新疆大学教授。E-mail:xynan@xju.edu.cn
  • 基金资助:
    国家自然科学基金(52065064)

Trajectory Tracking Control Based on Model-Free Coordinate Compensation Integral Sliding Mode Constraints

LU Xumeng, NAN Xinyuan*, XIA Sibo   

  1. School of Electrical Engineering, Xinjiang University, Urumqi Xinjiang 830047, China
  • Received:2022-04-20 Revised:2022-06-03 Online:2023-03-25 Published:2023-04-25

摘要: 为了解决四轮自动驾驶汽车轨迹跟踪的复杂控制问题,提出一种新的全格式无模型自适应坐标补偿积分滑模约束控制方案。控制方案只需要自动驾驶车辆轨迹跟踪的I/O数据,不涉及车辆模型信息,即前轮转角输入数据和车辆横摆角输出数据。因此,该方案对于不同车型均能实现轨迹跟踪控制。在轨迹跟踪过程中只针对车辆横摆角进行控制易造成跟踪轨迹偏差,本文在全格式无模型自适应控制的基础上加入坐标补偿算法;为了提高系统在运行过程中的鲁棒性,加入积分滑模控制;为了应对在滑模控制过程中系统运行在饱和区域,设计了动态补偿,使轨迹跟踪系统运行在滑模控制的线性区域。最后,对无模型自适应积分滑模约束控制方案、原型无模型自适应控制算法和PID算法进行仿真比较。仿真结果表明,所提算法比传统控制方法具有更好的控制性能,跟踪波动误差在0.09%以内,稳定时间在0.5 s以内,跟踪曲线平滑。

关键词: 自动驾驶, 轨迹跟踪, 坐标补偿, 全格式数据驱动控制, 积分滑模控制(SMC), 积分饱和补偿

Abstract: In order to solve the complex control problem of the trajectory tracking of four-wheel autonomous vehicles, a new full model-free adaptive coordinate compensation integral sliding mode constraint control scheme is proposed. The control scheme only needs the I/O data of the trajectory tracking of the autonomous driving vehicle, and does not involve the vehicle model information, that is, the input data of the front wheel angle and the output data of the body angle. Therefore, this new scheme can realize trajectory tracking control for the trajectory tracking systems of different vehicle models. In the process of trajectory tracking, only controlling the body angle is easy to cause the deviation of the tracking trajectory. In this paper, firstly, a coordinate compensation algorithm is added on the basis of the full-format model-free adaptive control. Secondly, in order to improve the robustness of the system during operation, an integral sliding mode control is added. Thirdly, to deal with the system running in the saturation region in the process of sliding mode control, dynamic compensation is designed to make the trajectory tracking system run in the linear region of sliding mode control. Finally, a simulation comparison among the model-free adaptive integral sliding mode constraint control scheme, the prototype model-free adaptive control algorithm and the PID algorithm is carried out. The results show that the proposed algorithm has better control performance than traditional control methods. The tracking fluctuation error is within 0.09%. The stabilization time is within 0.5 s, and the tracking curve is smooth.

Key words: self-driving, trajectory tracking, coordinate compensation, full format data driven control, integral sliding mode control (SMC), integral windup compensation

中图分类号: 

  • U463.6
[1] LIU K Z, HORII M. An experimental comparison of nonholonomic control methods: automatic parking benchmark[C]// SICE Annual Conference 2007. Piscataway, NJ: IEEE, 2007: 1712-1717.
[2] CHEN C H, HSU C W, YAO C C. A novel design for full automatic parking system[C]// 2012 12th International Conference on ITS Telecommunications. Piscataway, NJ: IEEE, 2012: 175-179.
[3] 许伦辉,刘景柠,朱群强,等.自动引导车路径偏差的控制研究[J].广西师范大学学报(自然科学版),2015,33(1):1-6.
[4] 王宏涛,蒋清泽,张强,等.轨迹跟踪的混合编码遗传优化模糊PID控制策略[J].哈尔滨工程大学学报,2021,42(7):1076-1082.
[5] 丁飞,黎乾龙,雷飞,等.动态轨迹跟踪下力矩相关性驱动辅助的人机协同转向预测控制策略研究[J].机械工程学报,2022,58(6):143-152.
[6] 梁启星, 李彬, 李志, 等. 基于模型预测控制的四足机器人斜坡自适应调整算法与实现[J]. 山东大学学报(工学版), 2021, 51(3): 37-44.
[7] 焦建芳,包端华,胡正中.基于预设性能的自适应神经网络船舶轨迹跟踪[J].华中科技大学学报(自然科学版),2022,50(4):77-82.
[8] 于欣波,贺威,薛程谦,等.基于扰动观测器的机器人自适应神经网络跟踪控制研究[J].自动化学报,2019,45(7):1307-1324.
[9] 唐志勇,马福源,裴忠才.四旋翼的改进PSO-RBF神经网络自适应滑模控制[J/OL].北京航空航天大学学报:1-14[2022-04-20].https://kns.cnki.net/kcms/detail/detail.aspx?FileName=BJHK20211210001&DbName=CAPJ2021.DOI: 10.13700/j.bh.1001-5965.2021.0477.
[10] ŠKRJANC I, KLANAR G. A comparison of continuous and discrete tracking-error model-based predictive control for mobile robots[J]. Robotics and Autonomous Systems, 2017, 87: 177-187.
[11] XU J X, HOU Z S. Notes on data-driven system approaches[J]. Acta Automatica Sinica, 2009, 35(6): 668-675.
[12] 王宏,柴天佑,丁进良,等.数据驱动的故障诊断与容错控制:进展与可能的新方向[J].自动化学报,2009,35(6):739-747.
[13] 江浩斌,冯张棋,洪阳珂,等.应用于车辆纵向控制的无模型自适应滑模预测控制方法[J].汽车工程,2022,44(3):319-329.
[14] 钟志贤,蔡忠侯,祁雁英.单自由度磁悬浮系统无模型自适应控制的研究[J].西南交通大学学报,2022,57(3):549-557,581.
[15] XU D Z, JIANG B, LIU F. Improved data driven model free adaptive constrained control for a solid oxide fuel cell[J]. IET Control Theory and Applications, 2016, 10(12): 1412-1419.
[16] 邓望权,田震,王子楠,等.基于PI与无模型自适应控制结合的燃气轮机转速控制方法[J].推进技术,2022,43(7):399-407.
[17] XU D Z, JIANG B, SHI P. Adaptive observer based data-driven control for nonlinear discrete-time processes[J]. IEEE Transactions on Automation Science and Engineering, 2014, 11(4): 1037-1045.
[18] PANG Z H, LIU G P, ZHOU D H, et al. Data-based predictive control for networked nonlinear systems with network-induced delay and packet dropout[J]. IEEE Transactions on Industrial Electronics, 2016, 63(2): 1249-1257.
[19] 王文佳,侯忠生.基于无模型自适应控制的自动泊车方案[J].控制与决策,2022,37(8):2056-2066.
[20] LIU J X, VAZQUEZ S, WU L G, et al. Extended state observer-based sliding-mode control for three-phase power converters[J]. IEEE Transactions on Industrial Electronics, 2017, 64(1): 22-31.
[21] 朱艺锋,李岩,张紫阳,等.含耦合电感的三相五电平整流器积分滑模控制[J/OL].高电压技术:1-10[2022-04-02].https://kns.cnki.net/kcms/detail/detail.aspx?FileName=GDYJ20220425010&DbName=DKFX2022. DOI: 10.13336/j.1003-6520.hve.20220145.
[22] LIU Y J, TONG S C, LI D J, et al. Fuzzy adaptive control with state observer for a class of nonlinear discrete-time systems with input constraint[J]. IEEE Transactions on Fuzzy Systems, 2016, 24(5): 1147-1158.
[23] DEMIRLI K, KHOSHNEJAD M. Autonomous parallel parking of a car-like mobile robot by a neuro-fuzzy sensor-based controller[J]. Fuzzy Sets and Systems, 2009, 160(19): 2876-2891.
[24] LIU K Z, DAO M Q, INOUE T. An exponentially ε-convergent control algorithm for chained systems and its application to automatic parking systems[J]. IEEE Transactions on Control Systems Technology, 2006, 14(6): 1113-1126.
[25] MULLER B, DEUTSCHER J, GRODDE S. Continuous curvature trajectory design and feedforward control for parking a car[J]. IEEE Transactions on Control Systems Technology, 2007, 15(3): 541-553.
[26] 侯忠生,董航瑞,金尚泰.基于坐标补偿的自动泊车系统无模型自适应控制[J].自动化学报,2015,41(4):823-831.
[27] LIU J X, WU C W, WANG Z H, et al. Reliable filter design for sensor networks using type-2 fuzzy framework[J]. IEEE Transactions on Industrial Informatics, 2017, 13(4): 1742-1752.
[28] SPOONER J T, MAGGIORE M, ORDÓÑEZ R, et al. Stable adaptive control and estimation for nonlinear systems: neural and fuzzy approximator techniques[M]. New York: John Wiley & Sons, Inc., 2002.
[29] 姚文龙,庞震,池荣虎,等.环卫车辆轨迹跟踪系统的无模型自适应迭代学习控制[J].控制理论与应用,2022,39(1):101-108.
[30] 王洪斌,左佳铄,刘世达,等.无人驾驶车辆稳态漂移的无模型自适应控制[J].控制理论与应用,2021,38(1):23-32.
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