On the Stability and Robustness of Hierarchical Vehicle Lateral Control With Inverse/Forward Dynamics Quasi-Cancellation

被引:9
作者
Dona, Riccardo [1 ]
Papini, Gastone Pietro Rosati [1 ]
Da Lio, Mauro [1 ]
Zaccarian, Luca [1 ,2 ]
机构
[1] Univ Trento, Dept Ind Engn, I-38122 Trento, Italy
[2] Univ Toulouse, CNRS, LAAS, F-31013 Toulouse, France
基金
欧盟地平线“2020”;
关键词
Advanced Driver Assistance Systems (ADAS); layered control; optimal control (OC); automated driving; vehicle dynamics; system stability; MODEL-PREDICTIVE CONTROL; AUTONOMOUS VEHICLES; PRINCIPLES; ROAD;
D O I
10.1109/TVT.2019.2941379
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 studies a control architecture for vehicle lateral dynamics based on the execution of optimal trajectories via feedforward inverse model control. The focus here is on assessing the robustness of this arrangement when the vehicle real forward dynamics is not identically cancelled by the inverse model due to model approximations and parameter uncertainties. The trajectories that are considered are analytic solutions of the minimum square jerk optimal control problem for a simplified kinematic vehicle model in curvilinear coordinates. Various hypotheses are made concerning the mismatch between the inverse model and the actual forward dynamics of the vehicle. Closed-loop stability analysis shows that the studied control scheme guarantees asymptotic stability of both the nominal and the perturbed kinematic model with significant robustness margins. In addition to the theoretical robustness analysis, the same control scheme is validated in simulation using the industry-standard software for virtual vehicle testing IPG CarMaker.
引用
收藏
页码:10559 / 10570
页数:12
相关论文
共 32 条
[1]  
Abe M., 2015, Vehicle Handling Dynamics
[2]  
[Anonymous], IEEE T INTELLIGENT V, DOI DOI 10.1109/TIV.2016.2578706
[3]  
[Anonymous], 2014, The Science of Vehicle Dynamics: Handling, Braking, and Ride of Road and Race Cars
[4]   Computational principles of sensorimotor control that minimize uncertainty and variability [J].
Bays, Paul M. ;
Wolpert, Daniel M. .
JOURNAL OF PHYSIOLOGY-LONDON, 2007, 578 (02) :387-396
[5]   Symbolic-numeric efficient solution of optimal control problems for multibody systems [J].
Bertolazzi, E ;
Biral, F ;
Da Lio, M .
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2006, 185 (02) :404-421
[6]   Symbolic-numeric indirect method for solving Optimal Control Problems for large multibody systems - The time-optimal racing vehicle example [J].
Bertolazzi, E ;
Biral, F ;
Da Lio, M .
MULTIBODY SYSTEM DYNAMICS, 2005, 13 (02) :233-252
[7]   Supporting Drivers in Keeping Safe Speed and Safe Distance: The SASPENCE Subproject Within the European Framework Programme 6 Integrating Project PReVENT [J].
Bertolazzi, Enrico ;
Biral, Francesco ;
Da Lio, Mauro ;
Saroldi, Andrea ;
Tango, Fabio .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2010, 11 (03) :525-538
[8]   A general method for the evaluation of vehicle manoeuvrability with special emphasis on motorcycles [J].
Cossalter, V ;
da Lio, M ;
Lot, R ;
Fabbri, L .
VEHICLE SYSTEM DYNAMICS, 1999, 31 (02) :113-135
[9]  
Da Lio M., 2018, DREAMS4CARS SYSTEM A
[10]  
Da Lio M., 2018, DREAMS4CARS REPORT R