Active suspension H ∞ /generalized H2 static output feedback control

被引:0
|
作者
Shi, Zhuqing [1 ]
Cao, Ruili [2 ]
Zhang, Shishuo [1 ]
Guo, Jie [1 ]
Yu, Shuyou [1 ,3 ,5 ,6 ]
Chen, Hong [1 ,4 ]
机构
[1] Jilin Univ, Dept Control Sci & Engn, Changchun, Peoples R China
[2] CRRC Zhuzhou Elect Co Ltd, Syst Integrat R&D Dept, Zhuzhou, Peoples R China
[3] Chongqing Univ Posts & Telecommun, Coll Automat, Chongqing, Peoples R China
[4] Tongji Univ, Coll Elect & Informat Engn, Shanghai, Peoples R China
[5] Jilin Univ, Dept Control Sci & Engn, Nanhu Rd 5372,Mail Box 9, Changchun 130025, Peoples R China
[6] Chongqing Univ Posts & Telecommun, Coll Automat, Chongqing 400065, Peoples R China
关键词
active suspension; H-infinity/GH(2) control; static output feedback control; HiL experiment; VEHICLE SUSPENSIONS; SYSTEMS;
D O I
10.1177/10775463231223271
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
This paper proposes an approach of H (infinity) /generalized H-2 (GH(2)) static output feedback control for vehicle active suspension. To address the conflicting performance requirements in active suspension, the H (infinity) norm is minimized to optimize the ride comfort performance, while the GH(2) norm is designed to meet time-domain hard constraints, including suspension stroke, road-holding performance, and actuator saturation. As not all states of active suspension are measurable in practice, the static output feedback control is designed using suspension stroke and sprung mass velocity as feedback signals. An invertible matrix condition is introduced in the static output feedback control design, which transforms the control problem into a convex optimization problem that can be solved using linear matrix inequalities (LMIs). Simulation and hardware-in-the-loop (HiL) experiments are conducted on both bump and random road responses for active and passive suspension of a 2-degree-of-freedom quarter vehicle. The proposed active suspension H (infinity) /GH(2 )static output feedback controller is compared with H (infinity) state feedback controller and the existing controller solved by LMIs and genetic algorithms (GAs), demonstrating that the proposed strategy achieves better ride comfort performance under various road conditions while satisfying all time-domain hard constraints.
引用
收藏
页数:13
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