Energy Dissipation Based Longitudinal and Lateral Coupling Control for Intelligent Vehicles

被引:9
作者
Zhang, Rui [1 ]
Ma, Yulin [2 ]
Li, Zhixiong [3 ,4 ]
Malekian, Reza [5 ]
Angel Sotelo, Miguel [6 ]
机构
[1] Tianjin Univ Technol & Educ, Sch Automot & Transportat, Tianjin 300222, Peoples R China
[2] Minist Transport, Res Inst Highway, Natl Ctr ITS Engn & Technol, Beijing 100088, Peoples R China
[3] China Univ Min & Technol, Sch Mech Engn, Xuzhou 221000, Peoples R China
[4] Iowa State Univ, Dept Mech Engn, Ames, IA 50010 USA
[5] Univ Pretoria, Dept Elect Elect & Comp Engn, ZA-0002 Pretoria, South Africa
[6] Univ Alcala, Dept Comp Engn, Alcala De Henares, Madrid, Spain
基金
中国国家自然科学基金;
关键词
ADAPTIVE CRUISE CONTROL; SYSTEMS;
D O I
10.1109/MITS.2018.2806623
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a combined longitudinal and lateral control approach for an intelligent vehicle system based on energy dissipation. The vehicle system dynamics resembles a series of mass/spring/damper systems that are dissipative, i.e., the energy of the system decays to zero eventually. Thus, the nonlinear-optimal longitudinal and lateral coupling control problem of the intelligent vehicle system is transformed into a dissipative control design based on an energy storage function. To satisfy the gamma-performance, with respect to the quadratic supply rate, the storage function is developed by using a back-stepping based Lyapunov method and a step-by-step improvement of performance bounds. A dissipative feedback control law is formulated by successive approximation based on the step-by-step reduction of the value of gamma. The results of the adaptive vehicle control simulations and test-bed experiments are provided and verified by the respective comparison of energy consumption on different values of c and speed adaption under different road geometries.
引用
收藏
页码:121 / 133
页数:13
相关论文
共 31 条
  • [1] Combined longitudinal and lateral control for automated vehicle guidance
    Attia, Rachid
    Orjuela, Rodolfo
    Basset, Michel
    [J]. VEHICLE SYSTEM DYNAMICS, 2014, 52 (02) : 261 - 279
  • [2] Corona D, 2006, IEEE INTL CONF CONTR, P90
  • [3] Garcia R., 2002, P INT VEH S VERS FRA, P3118
  • [4] A Review of Motion Planning Techniques for Automated Vehicles
    Gonzalez, David
    Perez, Joshue
    Milanes, Vicente
    Nashashibi, Fawzi
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (04) : 1135 - 1145
  • [5] Sampled-Data Cooperative Adaptive Cruise Control of Vehicles With Sensor Failures
    Guo, Ge
    Yue, Wei
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 15 (06) : 2404 - 2418
  • [6] Autonomous Platoon Control Allowing Range-Limited Sensors
    Guo, Ge
    Yue, Wei
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2012, 61 (07) : 2901 - 2912
  • [7] Experimental Application of Hybrid Fractional-Order Adaptive Cruise Control at Low Speed
    Hassan Hosseinnia, S.
    Tejado, Ines
    Milanes, Vicente
    Villagra, Jorge
    Vinagre, Blas M.
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2014, 22 (06) : 2329 - 2336
  • [8] Katriniok A, 2013, 2013 EUROPEAN CONTROL CONFERENCE (ECC), P974
  • [9] Kianfar R, 2014, 2014 IEEE 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), P1003, DOI 10.1109/ITSC.2014.6957819
  • [10] Split Covariance Intersection Filter: Theory and Its Application to Vehicle Localization
    Li, Hao
    Nashashibi, Fawzi
    Yang, Ming
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2013, 14 (04) : 1860 - 1871