A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter

2017 ◽  
Vol 66 ◽  
pp. 262-274 ◽  
Author(s):  
Yashar Shabbouei Hagh ◽  
Reza Mohammadi Asl ◽  
Vincent Cocquempot
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Fault Tolerant ◽  
Fault Tolerant Control

Sensor fault–tolerant control of a quadrotor unmanned aerial vehicle

2021 ◽  
pp. 095441002110155
Author(s):  
Mehmet Gokberk Patan ◽  
Fikret Caliskan
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Unscented Kalman Filter ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Sensor Faults ◽  
Cubature Kalman Filter ◽  
Non Linear ◽  
Aerial Vehicle

This article handles the issue of fault-tolerant control of a quadrotor unmanned aerial vehicle (UAV) in the existence of sensor faults. A general non-linear model of the quadrotor is presented. Several non-linear Kalman filters namely, the extended Kalman filter, the unscented Kalman filter and the cubature Kalman filter (CKF) are utilized to estimate the states of the quadrotor and to compare the estimation performances. Some flight scenarios are simulated, and the simulation results show that the CKF has the smallest estimation error as expected in theory. Control of the quadrotor heavily depends on the measured values received from sensors. Therefore, the control system requires fault-free sensors. However, small quadrotors and UAVs are mostly equipped with low-cost and low-quality sensors, and hence, they may fail to indicate correct measurement values. If the sensors are faulty, then the control system itself should be actively tolerant to sensor faults. Measurements of these kinds of sensors suffer from bias and external noise due to temperature variations, vibration and other external conditions. Since the bias is one of the very common faults in these sensors, a sensor bias is taken into consideration as a fault and occurs abruptly at a certain time and continues throughout the considered scenarios. By using the residual signals generated by the non-linear filters, sensor faults are detected and isolated. Then, two different methods are proposed for removing the effects of faults and achieving active fault–tolerant control. The effectiveness of the presented two techniques is shown in the simulations.

Fault Tolerant Control of an Industrial Gas Turbine Based on a Hybrid Fuzzy Adaptive Unscented Kalman Filter

2013 ◽  
Vol 135 (12) ◽  
Author(s):  
Amin Mirzaee ◽  
Karim Salahshoor
Keyword(s):  
Kalman Filter ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Unscented Kalman Filter ◽  
Fault Tolerant ◽  
Fuzzy Model ◽  
Fault Tolerant Control ◽  
The Core ◽  
Adaptive Unscented Kalman Filter ◽  
Industrial Gas Turbine

Gas turbines are generally used in power generation, the oil and gas industries, and as jet engines in aircrafts. Fault tolerance and reliability is important in such applications. Thus, accurate modeling and control system design is necessary. In this paper, first a nonlinear hybrid fuzzy model was developed for an industrial gas turbine, and then this model was used as the core of a fault tolerant control (FTC) system. The aforementioned model was trained by use of three months of operational data of a GE MS 5002 D gas turbine that is used for gas injection application, then it was fine tuned using expert knowledge and physical principles. A graphical user interface (GUI) was also developed to run various realistic operational scenarios of the gas turbine. The main point of the present work consists in introducing nonlinear fuzzy model schemes as the core of an adaptive unscented Kalman filter (AUKF) for fault diagnostic purposes. Analysis of the simulation results discloses that this FTC approach alleviates the effects of faults in two different scenarios such as sequential drift and bias in sensors/actuators and also in simultaneous faults that are a disastrous situation.

scholarly journals Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2972 ◽  
Author(s):  
Waseem El Sayed ◽  
Mostafa Abd El Geliel ◽  
Ahmed Lotfy
Keyword(s):  
Kalman Filter ◽  
Fault Diagnosis ◽  
Extended Kalman Filter ◽  
Continuous Monitoring ◽  
Unscented Kalman Filter ◽  
Fault Tolerant ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Practical Implementation ◽  
Complete Failure

Since the permeant magnet synchronous generator (PMSG) has many applications in particular safety-critical applications, enhancing PMSG availability has become essential. An effective tool for enhancing PMSG availability and reliability is continuous monitoring and diagnosis of the machine. Therefore, designing a robust fault diagnosis (FD) and fault tolerant system (FTS) of PMSG is essential for such applications. This paper describes an FD method that monitors online stator winding partial inter-turn faults in PMSGs. The fault appears in the direct and quadrature (dq)-frame equations of the machine. The extended Kalman filter (EKF) and unscented Kalman filter (UKF) were used to detect the percentage and the place of the fault. The proposed techniques have been simulated for different fault scenarios using Matlab®/Simulink®. The results of the EKF estimation responses simulation were validated with the practical implementation results of tests that were performed with a prototype PMSG used in the Arab Academy For Science and Technology (AAST) machine lab. The results showed impressive responses with different operating conditions when exposed to different fault states to prevent the development of complete failure.

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