[1]张家旭,周时莹,周洪亮,等.未知时变扰动下的车轮滑移率鲁棒非线性跟踪控制[J].东南大学学报(自然科学版),2020,50(6):1128-1133.[doi:10.3969/j.issn.1001-0505.2020.06.020]
　Zhang Jiaxu,Zhou Shiying,Zhou Hongliang,et al.Robust nonlinear tracking control of wheel slip with unknown time-varying disturbance[J].Journal of Southeast University (Natural Science Edition),2020,50(6):1128-1133.[doi:10.3969/j.issn.1001-0505.2020.06.020]
点击复制

未知时变扰动下的车轮滑移率鲁棒非线性跟踪控制()
分享到：

《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
50
期数:
2020年第6期
页码:
1128-1133
栏目:
交通运输工程
出版日期:
2020-11-20

文章信息/Info

Title:
Robust nonlinear tracking control of wheel slip with unknown time-varying disturbance
作者:
张家旭1; 2; 周时莹2; 周洪亮3; 赵健1; 朱冰1
1吉林大学汽车仿真与控制国家重点实验室, 长春 130022; 2中国第一汽车集团有限公司智能网联开发院, 长春 130011; 3哈尔滨工业大学航天学院, 哈尔滨 150001
Author(s):
Zhang Jiaxu1; 2;  Zhou Shiying2;  Zhou Hongliang3;  Zhao Jian1;  Zhu Bing1
1State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
2Intelligent Network Research and Development, China FAW Group Co., Ltd., Changchun 130011, China
3School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
关键词:
车辆工程;  车轮滑移率跟踪控制;  快速终端滑模控制;  有限时间稳定;  非线性干扰观测器
Keywords:
vehicle engineering;  wheel slip tracking control;  fast terminal sliding mode control;  finite-time stability;  nonlinear disturbance observer
分类号:
U461.1
DOI:
10.3969/j.issn.1001-0505.2020.06.020
摘要:
针对自动驾驶电动汽车对车轮滑移率跟踪控制的需求,提出一种对未知时变扰动具有强鲁棒性的车轮滑移率非线性跟踪控制策略.首先,基于Burckhardt轮胎模型建立车轮滑移率跟踪控制模型;随后,基于车轮滑移率跟踪控制模型设计非线性干扰观测器,通过在线估计和补偿未知时变扰动来提高系统的鲁棒性,并基于有限时间和快速终端滑模理论设计车轮滑移率鲁棒非线性跟踪控制律;最后,基于车辆动力学仿真软件,验证车轮滑移率鲁棒非线性跟踪控制策略的可行性和有效性.结果表明,该策略对未知时变扰动具有较强的鲁棒性,并且能够快速、准确和稳定地跟踪任意期望的连续车轮滑移率,车轮滑移率跟踪残差控制在0.32%以内,满足自动驾驶电动汽车的需求.
Abstract:
Aiming at the requirement of self-driving electric vehicle for wheel slip tracking control, a nonlinear wheel slip tracking control strategy with the robustness against the unknown time-varying disturbance was proposed. First, the wheel slip tracking control model was established based on the Burckhardt tire model. Then, based on the wheel slip tracking control model, a nonlinear disturbance observer was designed to improve the robustness of the system by the online estimation and the compensation for an unknown time-varying disturbance, and a robust nonlinear wheel slip tracking control law was designed based on the finite time and the fast terminal sliding mode theory. Finally, the feasibility and the validity of the robust nonlinear wheel slip tracking control strategy were verified by the vehicle dynamics simulation software. The results show that the proposed strategy has strong robustness against the unknown time-varying disturbance and can track any desired continuous wheel slip rapidly and steadily. The tracking residual of the wheel slip can be controlled within 0.32%, thus meeting the requirements of self-driving electric vehicles.

参考文献/References:

[1] 张家旭,施正堂,杨雄,等.基于Elman神经网络的车轮滑移率跟踪控制[J].华中科技大学学报(自然科学版),2020,48(6):64-69. DOI:10.13245/j.hust.200611.
Zhang J X, Shi Z T, Yang X, et al. Wheel slip tracking control of vehicle based on Elman neural network[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition), 2020, 48(6): 64-69. DOI:10.13245/j.hust.200611. (in Chinese)
[2] Satzger C, de Castro R. Predictive brake control for electric vehicles[J]. IEEE Transactions on Vehicular Technology, 2018, 67(2): 977-990. DOI:10.1109/TVT.2017.2751104.
[3] Kuo C Y, Yeh E C. A four-phase control scheme of an anti-skid brake system for all road conditions[J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 1992, 206(4): 275-283. DOI:10.1243/pime_proc_1992_206_188_02.
[4] Pasillas-Lépine W. Hybrid modeling and limit cycle analysis for a class of five-phase anti-lock brake algorithms[J]. Vehicle System Dynamics, 2006, 44(2): 173-188. DOI:10.1080/00423110500385873.
[5] Tanelli M, Osorio G, di Bernardo M, et al. Existence, stability and robustness analysis of limit cycles in hybrid anti-lock braking systems[J]. International Journal of Control, 2009, 82(4): 659-678. DOI:10.1080/00207170802203598.
[6] 王伟达,丁能根,张为,等.ABS逻辑门限值自调整控制方法研究与试验验证[J].机械工程学报,2010,46(22):90-95,104. DOI:10.3901/JME.2010.22.090.
Wang W D, Ding N G, Zhang W, et al. Research and verification of the logic threshold self-adjusting control method for ABS[J]. Journal of Mechanical Engineering, 2010, 46(22): 90-95, 104. DOI:10.3901/JME.2010.22.090. (in Chinese)
[7] 张家旭,杨雄,施正堂,等.基于新型跟踪微分器的车轮滑移率跟踪控制[J].东南大学学报(自然科学版),2020,50(4):767-774. DOI:10.3969/j.issn.1001-0505.2020.04.022.
Zhang J X, Yang X, Shi Z T, et al. Tracking control of wheel slip based on new tracking differentiator[J]. Journal of Southeast University(Natural Science Edition), 2020, 50(4): 767-774. DOI:10.3969/j.issn.1001-0505.2020.04.022. (in Chinese)
[8] Johansen T A, Petersen I,Kalkkuhl J, et al. Gain-scheduled wheel slip control in automotive brake systems[J]. IEEE Transactions on Control Systems Technology, 2003, 11(6): 799-811. DOI:10.1109/TCST.2003.815607.
[9] Park K S, Lim J T. Wheel slip control for ABS with time delay input using feedback linearization and adaptive sliding mode control[C]//2008 International Conference on Control, Automation and Systems. October 14-17, 2008, Seoul, South Korea. New York: IEEE, 2008: 268-273. DOI:10.1109/ICCAS.2008.4694658.
[10] Amodeo M, Ferrara A,Terzaghi R, et al. Wheel slip control via second-order sliding-mode generation[J]. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(1): 122-131. DOI:10.1109/TITS.2009.2035438.
[11] Mirzaei M, Mirzaeinejad H. Optimal design of a non-linear controller for anti-lock braking system[J]. Transportation Research Part C: Emerging Technologies, 2012, 24: 19-35. DOI:10.1016/j.trc.2012.01.008.
[12] Yu H X,Qi Z Q, Duan J M, et al. Multiple model adaptive backstepping control for antilock braking system based on LuGre dynamic tyre model[J]. International Journal of Vehicle Design, 2015, 69(1/2/3/4): 168-184. DOI:10.1504/ijvd.2015.073120.
[13] Zhang J X, Li J. Adaptive backstepping sliding mode control for wheel slip tracking of vehicle with uncertainty observer[J]. Measurement and Control, 2018, 51(9/10): 396-405. DOI:10.1177/0020294018795321.
[14] Kiencke U, Nielsen L. Automotive control systems[M]. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005: 319-320. DOI:10.1007/b137654.
[15] Chen W H,Ballance D J, Gawthrop P J, et al. A nonlinear disturbance observer for robotic manipulators[J]. IEEE Transactions on Industrial Electronics, 2000, 47(4): 932-938. DOI:10.1109/41.857974.
[16] Yang L, Yang J Y. Nonsingular fast terminal sliding-mode control for nonlinear dynamical systems[J].International Journal of Robust and Nonlinear Control, 2011, 21(16): 1865-1879. DOI:10.1002/rnc.1666.
[17] Bhat S P, Bernstein D S. Continuous finite-time stabilization of the translational and rotational double integrators[J].IEEE Transactions on Automatic Control, 1998, 43(5): 678-682. DOI:10.1109/9.668834.
[18] Song J. Performance evaluation of a hybrid electric brake system with a sliding mode controller[J].Mechatronics, 2005, 15(3): 339-358. DOI:10.1016/j.mechatronics.2004.09.005.

相似文献/References:

[1]王海,蔡英凤,陈龙,等.基于Haar-NMF特征和改进SOMPNN的车辆检测算法[J].东南大学学报(自然科学版),2016,46(3):499.[doi:10.3969/j.issn.1001-0505.2016.03.008]
　Wang Hai,Cai Yingfeng,Chen Long,et al.Vehicle detection algorithm based on Haar-NMF features and improved SOMPNN[J].Journal of Southeast University (Natural Science Edition),2016,46(6):499.[doi:10.3969/j.issn.1001-0505.2016.03.008]
[2]张家旭,杨雄,施正堂,等.基于新型跟踪微分器的车轮滑移率跟踪控制[J].东南大学学报(自然科学版),2020,50(4):767.[doi:10.3969/j.issn.1001-0505.2020.04.022]
　Zhang Jiaxu,Yang Xiong,Shi Zhengtang,et al.Tracking control of wheel slip based on new tracking differentiator[J].Journal of Southeast University (Natural Science Edition),2020,50(6):767.[doi:10.3969/j.issn.1001-0505.2020.04.022]

备注/Memo

备注/Memo:
收稿日期: 2020-04-08.
作者简介: 张家旭(1985—),男,博士;赵健(联系人),男,博士,教授,博士生导师, zhaojian@jlu.edu.cn.
基金项目: 国家自然科学基金资助项目(51775235)、国家重点研发计划资助项目(2018YFB0105103).
引用本文: 张家旭,周时莹,周洪亮,等.未知时变扰动下的车轮滑移率鲁棒非线性跟踪控制[J].东南大学学报(自然科学版),2020,50(6):1128-1133. DOI:10.3969/j.issn.1001-0505.2020.06.020.
更新日期/Last Update: 2020-11-20