Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics

doi:10.1007/s11465-018-0486-x

Front. Mech. Eng.

2018, Vol. 13

Issue (3) : 354-367 https://doi.org/10.1007/s11465-018-0486-x

RESEARCH ARTICLE

Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics

Keqiang LI¹, Feng GAO²(

), Shengbo Eben LI¹(

), Yang ZHENG³, Hongbo GAO¹

¹. State Key Laboratory of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China
². School of Automotive Engineering, Chongqing University, Chongqing 400044, China
³. Department of Engineering Science, University of Oxford, Oxford OX13PJ, UK

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Abstract

This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range. With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.

Keywords automated vehicles platoon distributed control robustness

Corresponding Author(s): Feng GAO,Shengbo Eben LI

Just Accepted Date: 15 November 2017 Online First Date: 26 December 2017 Issue Date: 11 June 2018

Cite this article:

Keqiang LI,Feng GAO,Shengbo Eben LI, et al. Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics[J]. Front. Mech. Eng., 2018, 13(3): 354-367.

URL:

https://academic.hep.com.cn/fme/EN/10.1007/s11465-018-0486-x
https://academic.hep.com.cn/fme/EN/Y2018/V13/I3/354

Fig.1 Heterogeneous vehicular platoon with V2V

Fig.2 Vehicle dynamics and its inverse model

Parameters		Units	Nominal value	Uncertainty
Vehicle parameter	M	kg	1300	±15%
	$η T$	?	0.89	±5%
	i_f	?	4.43	?
	i_g	?	[2.71,1.44,1,0.74]	?
	r	m	0.28	?
	K_b	N·m/MPa	1185	±10%
	$τ b$	s	0.15	±15%
	$τ e$	s	0.3	±15%
	C_A	kg/m	0.2835	±10%
	f	?	0.02	±10%
	g	m/s²	9.81	?
Working point and environmental disturbance	v	m/s	?	3?30
	$ρ$	rad	0	?0.15?0.15
	v_w	m/s	0	?4?4

Tab.1 Key lumped parameters of a typical passenger car

Fig.3 Procedure to identify uncertain model

Fig.4 Identified bode plots at different setting points. (a) Time response of identification; (b) amplitude-frequency curve; (c) phase–frequency curve

Fig.5 Examples of typical communication topologies. (a) Leader following topology; (b) bidirectional topology

Fig.6 Topological decoupling procedure of vehicular platoon system. (a) Coupled system; (b) decoupled system

Fig.7 Bench test system

Fig.8 Virtual scenario of platoon driving in Prescan

Fig.9 Profiles of the lead vehicle. (a) Acceleration of leader; (b) vehicle speed of leader

Fig.10 Possibility function of successful communication with the parameter of distance between communicating vehicles

Fig.11 One period of added external resistances. (a) Wind speed; (b) road slope

Fig.12 Statistical results of communication, which is uncertain and time varying. (a) Possibility of successful connection; (b) distribution of eigenvalues

Fig.13 Maximum and minimum tracking errors under different test conditions. (a) Distance error under normal condition; (b) distance error under disturbed condition; (c) speed error under normal condition; (d) speed error under disturbed condition; (e) acceleration error under normal condition; (f) acceleration error under disturbed condition

Fig.14 Performance limit analysis results. (a) RMS of distance tracking error (unit: dB·m); (b) RMS of speed tracking error (unit: dB·m·s^?¹)

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