Fractional Network-Based Control for Vehicle Speed Adaptation via Vehicle-to-Infrastructure Communications

被引:17
作者
Tejado, Ines [1 ]
Milanes, Vicente [2 ]
Villagra, Jorge [2 ]
Vinagre, Blas M. [1 ]
机构
[1] Univ Extremadura, Sch Ind Engn, Badajoz 06006, Spain
[2] UPM, CSIC, CAR, AUTOPIA Program, Madrid 28500, Spain
关键词
Adaptive control; delay effects; fractional calculus; networked control systems (NCSs); vehicle driving; vehicle safety; velocity control; SYSTEMS;
D O I
10.1109/TCST.2012.2195494
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper addresses the problem of e-safety driving in urban areas, where the principal limiting factor is vehicle-to-vehicle or vehicle-to-infrastructure communications. Time-varying network-induced delays constitute the main concern of networked control systems since they may negatively affect the velocity control of a vehicle at low speeds and consequently cause an accident. A system to adapt the vehicle's speed to avoid or mitigate possible accidents has been developed. In particular, gain scheduling is used in a local fractional-order proportional integral controller to compensate the effects of delay. Experimental results on a prototype Citroen vehicle in a real environment are presented, which demonstrate the effectiveness of the proposed system.
引用
收藏
页码:780 / 790
页数:11
相关论文
共 50 条
[31]   DYNAMICAL INVESTIGATION AND DISTRIBUTED CONSENSUS TRACKING CONTROL OF A VARIABLE-ORDER FRACTIONAL SUPPLY CHAIN NETWORK USING A MULTI-AGENT NEURAL NETWORK-BASED CONTROL METHOD [J].
Sun, Tian-Chuan ;
Yousefpour, Amin ;
Karaca, Yeliz ;
Alassafi, Madini O. ;
Ahmad, Adil M. ;
Li, Yong-Min .
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY, 2022, 30 (05)
[32]   The Application of Fuzzy Neural Networks Based on Genetic Optimization Algorithm in Intelligent Vehicle Speed Control System [J].
Dong, Xiucheng ;
Yang, Xu .
PROCEEDINGS OF THE 2011 INTERNATIONAL CONFERENCE ON INFORMATICS, CYBERNETICS, AND COMPUTER ENGINEERING (ICCE2011), VOL 2: INFORMATION SYSTEMS AND COMPUTER ENGINEERING, 2011, 111 :367-375
[33]   The application of fuzzy neural networks based on genetic optimization algorithm in intelligent vehicle speed control system [J].
Dong X. ;
Yang X. .
Advances in Intelligent and Soft Computing, 2011, 111 :367-375
[34]   The Application of Fuzzy Neural Networks Based on Genetic Optimization Algorithm in Intelligent Vehicle Speed Control System [J].
Dong, Xiucheng ;
Yang, Xu .
2010 INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT (CCCM2010), VOL II, 2010, :197-200
[35]   Recurrent Neural Network-Based Robust Adaptive Model Predictive Speed Control for PMSM With Parameter Mismatch [J].
Nguyen, Ty Trung ;
Tran, Hoang Ngoc ;
Nguyen, Ton Hoang ;
Jeon, Jae Wook .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2023, 70 (06) :6219-6228
[36]   Control Strategy of Permanent Magnet Synchronous Motor for Electric Vehicle Based on Wavelet Neural Network [J].
Zong, Shasha ;
Liu, Zhizhen ;
Fan, Shujing ;
Liu, Zhenyou ;
Liu, Guoping ;
Hou, Yanjin .
PROCEEDINGS OF 2020 IEEE 4TH INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2020), 2020, :366-370
[37]   An Autonomous Vehicle Stability Control Using Active Fault-Tolerant Control Based on a Fuzzy Neural Network [J].
Alsuwian, Turki ;
Usman, Mian Hamza ;
Amin, Arslan Ahmed .
ELECTRONICS, 2022, 11 (19)
[38]   Observer-Based Adaptive Neural Network Trajectory Tracking Control for Remotely Operated Vehicle [J].
Chu, Zhenzhong ;
Zhu, Daqi ;
Yang, Simon X. .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (07) :1633-1645
[39]   Attack angle tracking for high speed vehicle based on variable structure and Taylor type FLNN neural network [J].
Song, Chuang ;
Lei, Junwei ;
Wu, Huali .
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2018, 35 (01) :283-291
[40]   Stabilisation of singularly perturbed nonlinear systems via neural network-based control and observer design [J].
Lin, Kuo-Jung .
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2013, 44 (10) :1925-1933