Sensor/Control Surface Fault Detection and Reconfiguration using Fuzzy Logic

被引:0
|
作者
Savanur, Shobha R. [1 ]
Patel, Ambalal V. [2 ]
机构
[1] BLDEAs Coll Engn & Technol, Bijapur, Karnataka, India
[2] Aeronaut Dev Agcy, Bangalore, Karnataka, India
关键词
Fuzzy logic; SFDIR; sensor fault detection isolation and reconfiguration; fault reconfiguration; sensor fault detection; control surface fault detection; Kalman filter;
D O I
10.14429/dsj.60.114
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In the aircraft night control systems, a quick detection of the faults, that occur in actuators, control surfaces or sensors, is necessary. In this paper, sensor fault detection and reconfiguration is performed using Kalman filter by estimating the states of the plant and comparing them with respective measured values from the sensors. Sensor fault detection and reconfiguration is carried out using non-model-based fuzzy logic technique. Control surface fault detection and reconfiguration is carried out by identifying the elements of control distribution matrix using extended Kalman filter and fuzzy logic. In estimating the factor of effectiveness of the control surface using fuzzy logic, different implication methods such as Mamadani's minimum, Larsen's product, bounded product and drastic product have been used and a comparison is made.
引用
收藏
页码:76 / 86
页数:11
相关论文
共 50 条
  • [1] AIRCRAFT ENGINE SENSOR FAULT DETECTION, ISOLATON AND RECONFIGURATION USING FUZZY LOGIC CONTROL BASED UNKNOWN INPUT OBSERVER
    Yazar, I.
    Kiyak, E.
    [J]. 10TH EUROPEAN CONFERENCE ON TURBOMACHINERY: FLUID DYNAMICS AND THERMODYNAMICS, 2013,
  • [2] Fault detection and diagnosis of photovoltaic system using fuzzy logic control
    Zaki, Sayed A.
    Zhu, Honglu
    Yao, Jianxi
    [J]. 2019 4TH INTERNATIONAL CONFERENCE ON SUSTAINABLE AND RENEWABLE ENERGY ENGINEERING (ICSREE 2019), 2019, 107
  • [3] Sensor/control surface fault diagnosis and reconfiguration in aircraft control systems
    Hajiyev, C
    Caliskan, F
    [J]. ENGINEERING, CONSTRUCTION AND OPERATIONS IN CHALLENGING ENVIRONMENTS: EARTH AND SPACE 2004, 2004, : 176 - 183
  • [4] Multiple signal fault detection using fuzzy logic
    Murphey, YL
    Crossman, J
    Chen, ZH
    [J]. DEVELOPMENTS IN APPLIED ARTIFICIAL INTELLIGENCE, 2003, 2718 : 83 - 92
  • [5] Fault Detection Using Difference Flatness and Fuzzy Logic
    Zhang, Nan
    Achaibou, Karim
    Mora-Camino, Felix
    [J]. ENGINEERING LETTERS, 2010, 18 (02)
  • [6] Fault Detection in Hydraulic System Using Fuzzy Logic
    Kulkarni, Manali
    Abou, Seraphin C.
    Stachowicz, Marian
    [J]. WCECS 2009: WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE, VOLS I AND II, 2009, : 966 - +
  • [7] EKF based surface fault detection and reconfiguration in aircraft control systems
    Caliskan, F
    Hajiyev, CM
    [J]. PROCEEDINGS OF THE 2000 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2000, : 1220 - 1224
  • [8] Fault detection in internal combustion engines using fuzzy logic
    Celik, M. B.
    Bayir, R.
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2007, 221 (D5) : 579 - 587
  • [9] Fault Detection and Protection of Induction Motor Using Fuzzy Logic
    Surwase, D. A.
    Jalit, A. S.
    Chavan, M. D.
    [J]. 2017 INTERNATIONAL CONFERENCE ON INNOVATIONS IN ELECTRICAL, ELECTRONICS, INSTRUMENTATION AND MEDIA TECHNOLOGY (ICIEEIMT), 2017, : 66 - 70
  • [10] High Impedance Fault Detection using Fuzzy Logic Technique
    Vyshnavi, Gogula
    Prasad, Avagaddi
    [J]. INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING, 2018, 11 (09): : 13 - 22