Observer-based event-triggered control of steer-by-wire systems with prespecified tracking accuracy

被引:13
作者
Ma, Bingxin [1 ]
Luo, Gang [1 ]
Wang, Yongfu [1 ]
机构
[1] Northeastern Univ, Sch Mech Engn & Automat, Shenyang 110819, Peoples R China
基金
中国国家自然科学基金;
关键词
Steer-by-wire (SbW) system; Adaptive state observer; Interval type-2 fuzzy logic system (IT2 FLS); Event-triggered finite-time control; Prespecified tracking accuracy; Vehicle experiment; SLIDING MODE CONTROL; TYPE-2; FUZZY-SETS; AUTONOMOUS VEHICLE; STABILIZATION; DESIGN;
D O I
10.1016/j.ymssp.2021.107857
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This paper addresses the event-triggered tracking control problem of the SbW system subject to unavailable steering angular velocity of front-wheels, time-varying external disturbance, and uncertain dynamics, including friction torque and self-aligning torque. First, an adaptive state observer is proposed to estimate the unavailable steering angular velocity of front-wheels. The uncertain nonlinearity and time-varying disturbance can be estimated by the adaptive interval type-2 fuzzy logic system (IT2 FLS) and the disturbance observer, respectively. An event-triggered control is proposed for SbW systems to guarantee the pre specified control performance and save communication resources in the controller-to actuator channel. Much importantly, the nested robust terms are incorporated in the control scheme to counteract the observation error and overcome the negative influence of the event-triggering error. Theoretical analysis shows that the prespecified arbitrary tracking accuracy can be guaranteed within finite time, and the Zeno-behavior can be strictly avoided while saving communication resources in the controller-to-actuator channel. Finally, simulation and vehicle experiment results and some comparisons are given to evaluate the effectiveness of the proposed method. (c) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页数:19
相关论文
共 62 条
[21]   Robust adaptive motion tracking of piezoelectric actuated stages using online neural-network-based sliding mode control [J].
Ling, Jie ;
Feng, Zhao ;
Zheng, Dongdong ;
Yang, Jun ;
Yu, Haoyong ;
Xiao, Xiaohui .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 150
[22]   Reliable Filter Design for Sensor Networks Using Type-2 Fuzzy Framework [J].
Liu, Jianxing ;
Wu, Chengwei ;
Wang, Zhenhuan ;
Wu, Ligang .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (04) :1742-1752
[23]   A Small-Gain Approach to Robust Event-Triggered Control of Nonlinear Systems [J].
Liu, Tengfei ;
Jiang, Zhong-Ping .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2015, 60 (08) :2072-2085
[24]   Trajectory Tracking Control of Autonomous Vehicle With Random Network Delay [J].
Luan, Zhongkai ;
Zhang, Jinning ;
Zhao, Wanzhong ;
Wang, Chunyan .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (08) :8140-8150
[25]   Fuzzy forecasting for long-term time series based on time-variant fuzzy information granules [J].
Luo Chao ;
Wang Haiyue .
APPLIED SOFT COMPUTING, 2020, 88
[26]   Adaptive Fuzzy Event-Triggered Control for Stochastic Nonlinear Systems With Full State Constraints and Actuator Faults [J].
Ma, Hui ;
Li, Hongyi ;
Liang, Hongjing ;
Dong, Guowei .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2019, 27 (11) :2242-2254
[27]   Second-Order Sliding Fuzzy Interval Type-2 Control for an Uncertain System With Real Application [J].
Manceur, Malik ;
Essounbouli, Najib ;
Hamzaoui, Abdelaziz .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2012, 20 (02) :262-275
[28]   Nested PID steering control for lane keeping in autonomous vehicles [J].
Marino, Riccardo ;
Scalzi, Stefano ;
Netto, Mariana .
CONTROL ENGINEERING PRACTICE, 2011, 19 (12) :1459-1467
[29]   An approach for parameterized shadowed type-2 fuzzy membership functions applied in control applications [J].
Melin, Patricia ;
Ontiveros-Robles, Emanuel ;
Gonzalez, Claudia I. ;
Castro, Juan R. ;
Castillo, Oscar .
SOFT COMPUTING, 2019, 23 (11) :3887-3901
[30]  
Mendel J., 2014, INTRO TYPE 2 FUZZY L