Actuator fault estimation and fault tolerant control for vehicle lateral dynamics

2019 ◽  
Author(s):  
N. El Youssfi ◽  
M. Oudghiri ◽  
R. El Bachtiri
2018 ◽  
Vol 51 (24) ◽  
pp. 709-716 ◽  
Author(s):  
Daniel A. Pereira ◽  
Ayad Al-Dujaili ◽  
Maan El Badaoui El Najjar ◽  
Vincent Cocquempot ◽  
Yajie Ma

Author(s):  
Kuo Ma ◽  
Zhengchao Xie ◽  
Pak Kin Wong ◽  
Wenfeng Li ◽  
Shaoqiang Chu ◽  
...  

Abstract This paper investigates the lateral dynamics stabilization problem for autonomous electric vehicles (AEVs) through the active front steering (AFS) system. A fault-estimation-observer-based robust fuzzy fault tolerant controller is proposed to tackle actuator faults, time delay, modeling nonlinearities and external disturbances. Firstly, to establish a more accurate dynamics model, the Takagi-Sugeno fuzzy modeling strategy is utilized to handle velocity change and parameter uncertainties. Secondly, to further improve the lateral stability and driving active safety of the AEV, an integrated actuator fault model comprising efficiency loss fault and additional bias fault is proposed. Meanwhile, in order to diagnose actuator additional bias fault, a fuzzy fault estimation observer (FFEO) is designed to acquire fault information online. Thirdly, to eliminate the influence caused by integrated fault and actuator time delay, a fuzzy fault tolerant controller (FFTC) is constructed to improve the handling performance and driving active safety of the AEV. Finally, the effectiveness of the proposed control scheme is demonstrated via a full-car model based on the joint simulation of Carsim and MATLAB/Simulink.


2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Abdelmounaim Khallouq ◽  
Asma Karama ◽  
Mohamed Abyad

Abstract This paper presents the problem of actuator fault estimation and fault-tolerant control (FTC) of a biological process using Takagi–Sugeno fuzzy formulation. The goal is to ensure the desired outputs tracking even if the time-varying actuator faults occur. We propose to use a proportional multi-integral (PMI) observer to estimate both the time-varying actuator faults and the state of system. The reconstructed faults are used to reconfigure the nominal controller. As a nominal control, we use a fuzzy linear quadratic integral (LQI) law. To ensure the global asymptotic convergence of the PMI observer and to improve the compensation speed of faults, we propose to use the multiple Lyapunov function by introducing a convergence rate. Sufficient conditions in terms of linear matrix inequalities (LMIs) are developed. The obtained results show that, the proposed approach is successfully applied to the problem of actuator fault-tolerant control of a bacterial growth process.


Author(s):  
Jinwei Sun ◽  
JingYu Cong ◽  
Liang Gu ◽  
Mingming Dong

As the possibility of sensor faults in the vehicle chassis system is higher and influences the vehicle stability, this paper deals with active fault-tolerant control for vehicle with vertical and lateral dynamics. It focuses on the combined control of active suspension system and electronic stability control with sensor faults based on the interaction between vehicle with vertical and lateral dynamics. A 9-degree-of-freedom vehicle integrated model is adopted for accurate control. The aim of the controller is to improve riding comfort when the vehicle is driving straight and improve lateral stability when the vehicle is steering in the presence of external disturbances and sensor faults. First, an H∞-based method is introduced to reconstruct the sensor fault signals, and meanwhile, the method can also observe the unmeasured signals. Based on the reconstruction faults and observed signals, a gain scheduling controller is utilized to guarantee the performance of the integrated model under different driving conditions, and the steering input is chosen as the scheduling parameter. Three different conditions, step steering input, single lane change input, and sensor faults, are considered. The main contributions of this study are as follows: (1) an H∞-based observer was designed for sensor fault estimation of the vertical and lateral integrated model and (2) a gain scheduling controller was designed to improve the performance of the integrated system. Simulations results indicated that the active fault-tolerant controller can reconstruct sensor faults and observe the unmeasured states exactly, and the linear parameter varying framework–based gain scheduling controller ensures the system performance adaptively.


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