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Adaptive guidance control of super-twisting sliding mode for virtual track train(PDF)


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Adaptive guidance control of super-twisting sliding mode for virtual track train
ZHANG Zhong-hua YANG Cai-jin ZHANG Wei-hua
(State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, Sichuan, China)
virtual track train adaptive super-twisting sliding mode guidance control gain coefficient unknown external disturbance wheel speed allocation
In order to improve the robust performance of autonomous guidance control of virtual track trains subject to parameter uncertainties and unknown external disturbances, the multi-input and multi-output overdrive control problem during train operation was studied, a nonlinear guidance control model of multi-articulated virtual track train was established based on Lagrange's formula, and the equivalent lateral tire force was used as the control input. By employing discrete point coordinates of the virtual track and the speed of the train, a reference model was built to calculate the location, speed, and acceleration of the train, and an independent guidance controller and longitudinal speed controller of the train were designed. By applying Lyapunov method, based on the traditional sliding mode control(SMC)and adaptive super-twisting sliding mode(ASTSM), two guidance controllers of the train were designed, respectively, and the control command of a steer-by-wire system was calculated by an inverse tire model. Moreover, a wheel speed allocation model was established, in which the longitudinal train speed control was converted to the speed and electromagnetic torque control of each in-wheel motor on the basis of the reference velocity vector. A dynamics simulation model composed of seven carriages was constructed, and the responses of in-wheel motor speed and electromagnetic torque were analyzed by variable speed and compound path test. The distribution law of the articulated force between vehicle modules was revealed, and the robustnesses of SMC and ASTSM under uncertain parameters and unknown external disturbances were compared. Research results show that the proposed guidance control model, motion reference model, and wheel speed allocation model are effective. The tracking errors of longitudinal velocities of vehicle modules are less than 1.5 km?h-1, and the tracking error rates of wheel speeds are not more than 1%. Compared with the SMC, the proposed ASTSM has better adaptive robustness in the presence of unmodeled dynamics, 50% load changes, and unknown disturbances, and the deviation of each axle center can gradually converge to around 0 in finite time. Under the lateral force interference, the root mean square deviation and maximum deviation of the ASTSM for all axis centers are 10 and 42 mm, and decrease by 82% and 61%, respectively. In addition, the steady-state deviation of the ASTSM on the curved section is not significant, and the articulated angles can consistently converge to a stable value, which guarantees the stability of the virtual track train. 1 tab, 19 figs, 31 refs.


[1] 冯江华.轨道交通装备技术演进与智能化发展[J].控制与信息技术,2019(1):1-6,11.
FENG Jiang-hua. Technical evolution and intelligent development of rail transit equipments[J]. Control and Information Technology, 2019(1): 1-6, 11.(in Chinese)
[2] YIN Zhong-hui, ZHANG Ji-ye, LU Hai-ying. Establishment and comparison of a spatial dynamics model for virtual track train with different steering modes[J]. Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-Body Dynamics, 2021, 235(3): 481-498.
[3] LENG Han, REN Li-hui, JI Yuan-jin. Cascade modular path following control strategy for gantry virtual track train: time-delay stability and forward predictive model[J]. IEEE Transactions on Vehicular Technology, 2022, 71(7): 6969-6983.
[4] 孙帮成,王文军,刘志明,等.基于全轮差动转向的虚拟轨道汽车列车设计[J].北京交通大学学报,2018,42(6):67-74.
SUN Bang-cheng, WANG Wen-jun, LIU Zhi-ming, et al. Design of the virtual-rail train-like vehicle based on all-wheel differential steering[J]. Journal of Beijing Jiaotong University, 2018, 42(6): 67-74.(in Chinese)
[5] 袁希文,冯江华,胡云卿,等.智轨电车自动循迹感知与控制系统[J].控制与信息技术,2020(1):19-26.
YUAN Xi-wen, FENG Jiang-hua, HU Yun-qing, et al. Perception and control module of the automatic tracking system for autonomous-rail rapid tram[J]. Control and Information Technology, 2020(1): 19-26.(in Chinese)
[6] 崔 涛,王 淇,刘学刚,等.虚拟轨道列车多轴协同预瞄循迹控制方法[J].北京交通大学学报,2022,46(1):139-146.
CUI Tao, WANG Qi, LIU Xue-gang, et al. Multi-axle coordination-based pre-targeting path-tracking control method for virtual railway vehicles[J]. Journal of Beijing Jiaotong University, 2022, 46(1): 139-146.(in Chinese)
[7] WANG Cheng-ping, ZHANG Ji-min, ZHOU He-chao, et al. Analysis of the running quality and road friendliness of the virtual track train in multiple running stages between stations[J]. Journal of Mechanical Science and Technology, 2022, 36(2): 593-605.
[8] YIN Zhong-hui, ZHANG Ji-ye, LU Hai-ying, et al. Dynamics modeling and analysis of a four-wheel independent motor-drive virtual-track train[J]. Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-Body Dynamics, 2021, 235(1): 134-149.
[9] YIN Zhong-hui, ZHANG Ji-ye, SUI Hao. Stochastic responses characteristics of a virtual track train excited by road irregularities[J]. IEEE Transactions on Vehicular Technology, 2022, 71(8): 8152-8163.
[10] 彭 京,冯江华,肖 磊,等.智轨电车自主导向与轨迹跟随技术研究[J].控制与信息技术,2020(1):27-31.
PENG Jing, FENG Jiang-hua, XIAO Lei, et al. Research on autonomous guidance and track following technology of autonomous-rail rapid tram[J]. Control and Information Technology, 2020(1): 27-31.(in Chinese)
[11] 孙帮成,刘志明,崔 涛,等.一种汽车列车结构及其路径跟踪控制方法[J].机械工程学报,2018,54(24):181-188.
SUN Bang-cheng, LIU Zhi-ming, CUI Tao, et al.New structure for train-like vehicle and its path tracking method[J]. Journal of Mechanical Engineering, 2018, 54(24): 181-188.(in Chinese)
[12] KANEKO T, IIZUKA H, KAGEYAMA I. Steering control for advanced guideway bus system with all-wheel steering system[J]. Vehicle System Dynamics, 2006, 44(1): 741-746.
[13] 张立伟,杨露明,宋佩佩,等.多铰接结构的现代无轨列车路径跟随研究[J].北京交通大学学报,2021,45(4):137-145.
ZHANG Li-wei, YANG Lu-ming, SONG Pei-pei, et al. Research on path following of modern trackless train with multi-articulated structure[J]. Journal of Beijing Jiaotong University, 2021, 45(4): 137-145.(in Chinese)
[14] LENG Han, REN Li-hui, JI Yuan-jin. Analysis methodology of compatibility between motion control and mechanical architecture of a newly designed gantry virtual track train and the path-tracking control strategy[J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2022, 236(13): 6985-7005.
[15] ESMAEILI N, KAZEMI R, TABATABAEI OREH S H. An adaptive sliding mode controller for the lateral control of articulated long vehicles[J]. Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-Body Dynamics, 2019, 233(3): 487-515.
[16] MARUMO Y, YOKOTA T, AOKI A. Improving stability and lane-keeping performance for multi-articulated vehicles using vector follower control[J]. Vehicle System Dynamics, 2020, 58(12): 1859-1872.
[17] ISLAM M M, DING Xue-jun, HE Yu-ping. A closed-loop dynamic simulation-based design method for articulated heavy vehicles with active trailer steering systems[J]. Vehicle System Dynamics, 2012, 50(5): 675-697.
[18] NI Zhi-tuo, HE Yu-ping. Design and validation of a robust active trailer steering system for multi-trailer articulated heavy vehicles[J]. Vehicle System Dynamics, 2019, 57(10): 1545-1571.
[19] LIU Xuan-zuo, MADHUSUDHANAN A K, CEBON D. Minimum swept-path control for autonomous reversing of a tractor semi-trailer[J]. IEEE Transactions on Vehicular Technology, 2019, 68(5): 4367-4376.
[20] RITZEN P, ROEBROEK E, VAN DE WOUW N, et al. Trailer steering control of a tractor-trailer robot[J]. IEEE Transactions on Control Systems Technology, 2016, 24(4): 1240-1252.
[21] CANALE M, FAGIANO L, FERRARA A, et al. Comparing internal model control and sliding-mode approaches for vehicle yaw control[J]. IEEE Transactions on Intelligent Transportation Systems, 2009, 10(1): 31-41.
[22] ZHAO Yu-zhuang, CHEN Si-zhong, SHIM T. Investigation of trailer yaw motion control using active front steer and differential brake[J]. SAE International Journal of Materials and Manufacturing, 2011, 4(1): 1057-1067.
[23] FALLAHA C J, SAAD M, KANAAN H Y, et al. Sliding-mode robot control with exponential reaching law[J]. IEEE Transactions on Industrial Electronics, 2011, 58(2): 600-610.
[24] 任殿波,张京明,崔胜民,等.车辆换道纵横向耦合控制[J].交通运输工程学报,2009,9(3):112-116.
REN Dian-bo, ZHANG Jing-ming,CUI Sheng-min, et al. Longitudinal and lateral coupling control for lane change[J].Journal of Traffic and Transportation Engineering, 2009, 9(3): 112-116.(in Chinese)
[25] SHTESSEL Y, TALEB M, PLESTAN F. A novel adaptive-gain supertwisting sliding mode controller: methodology and application[J]. Automatica, 2012, 48(5): 759-769.
[26] GONZALEZ T, MORENO J A, FRIDMAN L. Variable gain super-twisting sliding mode control[J]. IEEE Transactions on Automatic Control, 2012, 57(8): 2100-2105.
[27] MORENO J A, OSORIO M. Strict Lyapunov functions for the super-twisting algorithm[J]. IEEE Transactions on Automatic Control, 2012, 57(4): 1035-1040.
[28] HU Chuan, WANG Zhen-feng, QIN Ye-chen, et al. Lane keeping control of autonomous vehicles with prescribed performance considering the rollover prevention and input saturation[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(7): 3091-3103.
[29] JUJNOVICH B A, CEBON D. Path-following steering control for articulated vehicles[J]. Journal of Dynamic Systems, Measurement, and Control, 2013, 135(3): 031006.
[30] DARBA A, DE BELIE F, D' HAESE P, et al. Improved dynamic behavior in BLDC drives using model predictive speed and current control[J]. IEEE Transactions on Industrial Electronics, 2016, 63(2): 728-740.
[31] FASIL M, MIJATOVIC N, JENSEN B B, et al. Nonlinear dynamic model of PMBLDC motor considering core losses[J]. IEEE Transactions on Industrial Electronics, 2017, 64(12): 9282-9290.


Last Update: 2023-11-10