scholarly journals Sliding Mode Fault Tolerant Control for Unmanned Aerial Vehicle with Sensor and Actuator Faults

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 643 ◽  
Author(s):  
Juan Tan ◽  
Yonghua Fan ◽  
Pengpeng Yan ◽  
Chun Wang ◽  
Hao Feng

The unmanned aerial vehicle (UAV) has been developing rapidly recently, and the safety and the reliability of the UAV are significant to the mission execution and the life of UAV. Sensor and actuator failures of a UAV are one of the most common malfunctions, threating the safety and life of the UAV. Fault-tolerant control technology is an effective method to improve the reliability and safety of UAV, which also contributes to vehicle health management (VHM). This paper deals with the sliding mode fault-tolerant control of the UAV, considering the failures of sensor and actuator. Firstly, a terminal sliding surface is designed to ensure the state of the system on the sliding mode surface throughout the control process based on the simplified coupling dynamic model. Then, the sliding mode control (SMC) method combined with the RBF neural network algorithm is used to design the parameters of the sliding mode controller, and with this, the efficiency of the design process is improved and system chattering is minimized. Finally, the Simulink simulations are carried out using a fault tolerance controller under the conditions where accelerometer sensor, gyroscope sensor or actuator failures is assumed. The results show that the proposed control strategy is quite an effective method for the control of UAVs with accelerometer sensor, gyroscope sensor or actuator failures.

2018 ◽  
Vol 22 (3) ◽  
pp. 1163-1176
Author(s):  
Chaofang Hu ◽  
Lei Cao ◽  
Xianpeng Zhou ◽  
Binghan Sun ◽  
Na Wang

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jian Shen ◽  
Qingyu Zhu ◽  
Xiaoguang Wang ◽  
Pengyun Chen

In this paper, the typical fault estimation and dynamic analysis are presented for a leader-follower unmanned aerial vehicle (UAV) formation system with external disturbances. Firstly, a dynamic model with proportional navigation guidance (PNG) control of the UAV formation is built. Then, an intermediate observer design method is adopted to estimate the system states and faults simultaneously. Based on the graph theory, the topology relationship between each node in the UAV formation has been also analyzed. The estimator and the system error have been created. Moreover, the typical faults, including the components failure, airframe damage, communication failure, formation collision, and environmental impact, are also discussed for the UAV system. Based on the fault-tolerant strategy, five familiar fault models are proposed from the perspectives of fault estimation, dynamical disturbances, and formation cooperative control. With an analysis of the results of states and faults estimation, the actuator faults can be estimated precisely with component failure and wind disturbances. Furthermore, the basic dynamic characteristics of the UAV formation are discussed. Besides, a comparison of two cases related to the wind disturbance has been accomplished to verify the performance of the fault estimator and controller. The results illustrate the credibility and applicability of the fault estimation and dynamic control strategies for the UAV system which are proposed in this paper. Finally, an extension about the UAV formation prognostic health management system is expounded from the point of view of the fault-tolerant control, dynamic modeling, and multifault estimation.


2019 ◽  
Vol 42 (2) ◽  
pp. 198-213
Author(s):  
Chaofang Hu ◽  
Zelong Zhang ◽  
Xianpeng Zhou ◽  
Na Wang

In this paper, a novel asymptotic fuzzy adaptive nonlinear fault tolerant control (FTC) scheme is presented for the under-actuated dynamics of a quadrotor unmanned aerial vehicle (UAV) subject to diverse sensor faults. The proposed FTC approach can deal with both additive sensor faults (bias, drift, loss of accuracy) and multiplicative sensor fault (loss of effectiveness). The overall dynamics is separated into position loop and attitude loop for FTC controllers design. Combining uncertain parameters and external disturbances, the four types of faults occurring in velocity sensors and Euler angle rate sensors are transformed equivalently into the unknown nonlinear function vectors and uncertain control gains. Fuzzy logic systems are used to approximate the lumped nonlinear functions, and adaptive parameters are estimated online. Nussbaum technique is introduced to deal with the unknown control gains. For both control loops, FTC controllers are designed via command filter-based backstepping approach, in which sliding mode control is introduced to establish asymptotic stability. All tracking error signals of the closed-loop control system are proved to converge to zero asymptotically. Finally, simulation comparisons with other methods demonstrate the effectiveness of the proposed FTC approach for quadrotor UAV with sensor faults.


2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Kaijia Xue ◽  
Congqing Wang ◽  
Zhiyu Li ◽  
Hanxin Chen

Unmanned Aerial Vehicle (UAV) is a nonlinear dynamic system with uncertainties and noises. Therefore, an appropriate control system has an obligation to ensure the stabilization and navigation of UAV. This paper mainly discusses the control problem of quad-rotor UAV system, which is influenced by unknown parameters and noises. Besides, a sliding mode control based on online adaptive error compensation support vector machine (SVM) is proposed for stabilizing quad-rotor UAV system. Sliding mode controller is established through analyzing quad-rotor dynamics model in which the unknown parameters are computed by offline SVM. During this process, the online adaptive error compensation SVM method is applied in this paper. As modeling errors and noises both exist in the process of flight, the offline SVM one-time mode cannot predict the uncertainties and noises accurately. The control law is adjusted in real-time by introducing new training sample data to online adaptive SVM in the control process, so that the stability and robustness of flight are ensured. It can be demonstrated through the simulation experiments that the UAV that joined online adaptive SVM can track the changing path faster according to its dynamic model. Consequently, the proposed method that is proved has the better control effect in the UAV system.


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