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GRNN inverse system based decoupling control strategy for active front steering and hydro-pneumatic suspension systems of emergency rescue vehicle.

Authors :
Xu, Fei-xiang
Zhou, Chen
Liu, Xin-hui
Wang, Jun
Source :
Mechanical Systems & Signal Processing. Mar2022:Part B, Vol. 167, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

• The inverse system is proposed to eliminate the mutual influence between the AFS and HPS subsystems. • PID and GRNN inverse system are combined to realize the decoupling control of the vehicle chassis system. • Real vehicle tests are conducted to demonstrate the effectiveness of the decoupling control strategy. Aiming at eliminating the mutual interference and coupling between the active front steering (AFS) and hydro-pneumatic suspension (HPS) subsystems of the emergency rescue vehicle, this paper presents a neural network inverse system based decoupling control strategy, which consists of the neural network inverse system and PID feedback control strategy. At first, a three-degrees of freedom dynamics model of the vehicle is constructed, and the reversibility of the vehicle chassis system is analyzed by the Interactor algorithm. Then, the generalized regression neural network (GRNN) model is used to identify the vehicle chassis inverse system, which decouples the multivariable vehicle chassis system into two independent single input and single output systems. Next, this paper proposes a closed-loop compound controller for the single input and single output systems, which is designed based on the PID control strategy and GRNN inverse system to realize the feedback control of the vehicle chassis system, so that the vehicle can track the desired yaw rate and roll angle well. Simulations and experiments are conducted on the self-developed fire rescue prototype vehicle, and the results prove that the proposed decoupling control strategy can not only eliminate coupling between AFS and HPS subsystems of the vehicle chassis, but also make the vehicle have better handling stability than controlled by the integrated control. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08883270
Volume :
167
Database :
Academic Search Index
Journal :
Mechanical Systems & Signal Processing
Publication Type :
Academic Journal
Accession number :
153851774
Full Text :
https://doi.org/10.1016/j.ymssp.2021.108595