Robust Compensation Fault-Tolerant Control Based on Sensor Fault Estimation Using Augmented System for DC Motor

Author(s):  
Tan Van Nguyen ◽  
Nguyen Ho Quang ◽  
Cheolkeun Ha
2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Xiao He ◽  
Yamei Ju ◽  
Yang Liu ◽  
Bangcheng Zhang

The fault tolerant control problem for a DC motor system is investigated in a cloud environment. Packet dropout phenomenon introduced by the limited-capacity communication channel is considered. Actuator faults are taken into consideration and fault diagnosis and fault tolerant control methods towards actuator faults are proposed to enhance the reliability of the whole cloud-based DC motor system. The fault diagnosis unit is then established with purpose of obtaining fault information. When the actuator fault is detected by comparing the residual signal with a predefined threshold, a residual matching approach is utilized to locate the fault. The fault can be further estimated by a least-squares filter. Based on the fault estimation, a fault tolerant controller is designed to guarantee the stability as well as the control performance of the DC motor system. Simulation result on a DC motor system shows the efficiency of the fault tolerant control method proposed in this paper.


2018 ◽  
Vol 28 (2) ◽  
pp. 297-308 ◽  
Author(s):  
Marcin Pazera ◽  
Mariusz Buciakowski ◽  
Marcin Witczak

Abstract The paper deals with the problem of designing sensor-fault tolerant control for a class of non-linear systems. The scheme is composed of a robust state and fault estimator as well as a controller. The estimator aims at recovering the real system state irrespective of sensor faults. Subsequently, the fault-free state is used for control purposes. Also, the robust sensor fault estimator is developed in a such a way that a level of disturbances attenuation can be reached pertaining to the fault estimation error. Fault-tolerant control is designed using similar criteria. Moreover, a separation principle is proposed, which makes it possible to design the fault estimator and control separately. The final part of the paper is devoted to the comprehensive experimental study related to the application of the proposed approach to a non-linear twin-rotor system, which clearly exhibits the performance of the new strategy.


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.


2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Hao Wang ◽  
Lina Yao

A sensor fault diagnosis method based on learning observer is proposed for non-Gaussian stochastic distribution control (SDC) systems. First, the system is modeled, and the linear B-spline is used to approximate the probability density function (PDF) of the system output. Then a new state variable is introduced, and the original system is transformed to an augmentation system. The observer is designed for the augmented system to estimate the fault. The observer gain and unknown parameters can be obtained by solving the linear matrix inequality (LMI). The fault influence can be compensated by the fault estimation information to achieve fault-tolerant control. Sliding mode control is used to make the PDF of the system output to track the desired distribution. MATLAB is used to verify the fault diagnosis and fault-tolerant control results.


Sign in / Sign up

Export Citation Format

Share Document