Adaptive Bioinspired Preview Suspension Control With Constrained Velocity Planning for Autonomous Vehicles

被引:16
作者
Huang, Tenglong [1 ]
Wang, Jue [1 ]
Pan, Huihui [1 ,2 ]
机构
[1] Harbin Inst Technol, Res Inst Intelligent Control & Syst, Harbin 150001, Peoples R China
[2] Harbin Inst Technol, Robot Innovat Ctr Co Ltd, Harbin 150001, Peoples R China
来源
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES | 2023年 / 8卷 / 07期
基金
中国国家自然科学基金;
关键词
Adaptive preview suspension; autonomous vehicles; bioinspired dynamic; constrained velocity planning; energy-saving; SYSTEMS;
D O I
10.1109/TIV.2023.3273620
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Autonomous vehicles equipped with numerous advanced sensors are capable of obtaining road preview information, creating new opportunities for vehicle suspension systems. This article proposes a novel preview suspension control method from adaptive nonlinear control perspectives with less computational burden and is more realistic, unlike optimization-based works or existing linear state-space models-based results that neglected nonlinear terms. The X-shaped bio-inspired dynamics derived from animal or insect skeleton structures are introduced to reduce energy consumption by utilizing beneficial geometrical nonlinearities. Meanwhile, optimal velocity planning approach is investigated to balance vehicle passage time, vibration suppression, and longitudinal comfort by solving a multi-objective optimization problem with the aid of road preview information. Moreover, acceleration constraint reduces the search space and computing requirements, while ensuring planned velocity optimality. Simulation and experiment results are provided to demonstrate the effectiveness and advantages of the constructed energy-saving adaptive preview control framework with constrained velocity planning.
引用
收藏
页码:3925 / 3935
页数:11
相关论文
共 30 条
[1]   Output feedback H/GH 2 preview control of active vehicle suspensions: a comparison study of LQG preview [J].
Akbari, Ahmad ;
Lohmann, Boris .
VEHICLE SYSTEM DYNAMICS, 2010, 48 (12) :1475-1494
[2]  
[Anonymous], 2001, 2001011063 SAE
[3]   Future Directions of Intelligent Vehicles: Potentials, Possibilities, and Perspectives [J].
Cao, Dongpu ;
Wang, Xiao ;
Li, Lingxi ;
Lv, Chen ;
Na, Xiaoxiang ;
Xing, Yang ;
Li, Xuan ;
Li, Ying ;
Chen, Yuanyuan ;
Wang, Fei-Yue .
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2022, 7 (01) :7-10
[4]   Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys [J].
Chen, Long ;
Li, Yuchen ;
Huang, Chao ;
Li, Bai ;
Xing, Yang ;
Tian, Daxin ;
Li, Li ;
Hu, Zhongxu ;
Na, Xiaoxiang ;
Li, Zixuan ;
Teng, Siyu ;
Lv, Chen ;
Wang, Jinjun ;
Cao, Dongpu ;
Zheng, Nanning ;
Wang, Fei-Yue .
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (02) :1046-1056
[5]   Design and Vehicle Implementation of Preview Active Suspension Controllers [J].
Goehrle, Christoph ;
Schindler, Andreas ;
Wagner, Andreas ;
Sawodny, Oliver .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2014, 22 (03) :1135-1142
[6]   Finite-Time Fault-Tolerant Integrated Motion Control for Autonomous Vehicles With Prescribed Performance [J].
Huang, Tenglong ;
Wang, Jue ;
Pan, Huihui ;
Sun, Weichao .
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2023, 9 (03) :4255-4265
[7]   Sine Resistance Network-Based Motion Planning Approach for Autonomous Electric Vehicles in Dynamic Environments [J].
Huang, Tenglong ;
Pan, Huihui ;
Sun, Weichao ;
Gao, Huijun .
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2022, 8 (02) :2862-2873
[8]   The X-structure/mechanism approach to beneficial nonlinear design in engineering [J].
Jing, Xingjian .
APPLIED MATHEMATICS AND MECHANICS-ENGLISH EDITION, 2022, 43 (07) :979-1000
[9]   In-situ adjustable nonlinear passive stiffness using X-shaped mechanisms [J].
Jing, Xingjian ;
Chai, Yuyang ;
Chao, Xu ;
Bian, Jing .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 170
[10]   Fuzzy Sampled-Data Control for Uncertain Vehicle Suspension Systems [J].
Li, Hongyi ;
Jing, Xingjian ;
Lam, Hak-Keung ;
Shi, Peng .
IEEE TRANSACTIONS ON CYBERNETICS, 2014, 44 (07) :1111-1126