Model reference FTC for LPV systems using virtual actuators and set-membership fault estimation

2014 ◽  
Vol 25 (5) ◽  
pp. 735-760 ◽  
Author(s):  
Damiano Rotondo ◽  
Fatiha Nejjari ◽  
Vicenç Puig ◽  
Joaquim Blesa
Keyword(s):  
Fault Estimation ◽  
Model Reference ◽  
Lpv Systems ◽  
Set Membership

scholarly journals Fault estimation for discrete time LPV systems under noisy scheduling measurements

2015 ◽  
Vol 48 (21) ◽  
pp. 1018-1023 ◽  
Author(s):  
Tamas Luspay ◽  
Balázs Kulcsár ◽  
Karolos Grigoriadis
Keyword(s):  
Discrete Time ◽  
Fault Estimation ◽  
Lpv Systems

ZKF-based optimal robust fault estimation of descriptor LPV systems with measurement error-affected scheduling variables

2019 ◽  
Vol 94 ◽  
pp. 119-134
Author(s):  
Junbo Tan ◽  
Feng Xu ◽  
Sorin Olaru ◽  
Xueqian Wang ◽  
Bin Liang
Keyword(s):  
Measurement Error ◽  
Fault Estimation ◽  
Lpv Systems

scholarly journals Fault detection for uncertain LPV systems using probabilistic set-membership parity relation

2020 ◽  
Vol 87 ◽  
pp. 27-36 ◽  
Author(s):  
Yiming Wan ◽  
Vicenç Puig ◽  
Carlos Ocampo-Martinez ◽  
Ye Wang ◽  
Eranda Harinath ◽  
...  
Keyword(s):  
Fault Detection ◽  
Lpv Systems ◽  
Set Membership ◽  
Parity Relation

Robust Model Reference Fault Detection and Identification System for Fixed Wing Aircrafts

2018 ◽  
Vol 10 (5) ◽  
Author(s):  
R. Jaganraj ◽  
R. Velu
Keyword(s):  
Fault Detection ◽  
Real Time ◽  
Fault Estimation ◽  
Identification System ◽  
Model Reference ◽  
Robust Model ◽  
Detection And Identification ◽  
Fault Detection And Identification ◽  
Time Parameters ◽  
Implantable Sensor

Fault Detection and Identification system (FDI) and Fault Tolerant Flight Control (FTFC) system are used to correct the faulty operation of an aircraft. Both FDIs and FTFCs have operational disadvantages due to their inherent limitation of fault source identification. This paper presents the design and implementation of a robust model reference fault detection and identification (MRFDI) system on a fixed-wing aircraft for identifying actuator fault, instrument fault and presence of any uncertainties. The proposed MRDFI fuses the real-time parameters and actuator feedback to combine the advantages of data driven and model reference FDI that makes robust fault estimation. The MRFDI system is implemented on a typical aircraft altitude hold autopilot simulation environment with a predefined fault scenario. The fault scenario includes a faulty elevator, a faulty skin-implantable sensor and wind gust as environmental uncertainty. The MRFDI performs logical analysis to detect fault using state-dependent real-time parameters and state-independent skin implantable sensor. This two-step fault detection method makes MRFDI robust to any type of fault identification. The results show that the MRFDI detects and distinguishes faults in actuator, instrument and any of the listed uncertainties thrown by the environment accurately.

Model reference control of LPV systems

2009 ◽  
Vol 346 (9) ◽  
pp. 854-871 ◽  
Author(s):  
Ali Abdullah ◽  
Mohamed Zribi
Keyword(s):  
Model Reference ◽  
Lpv Systems ◽  
Model Reference Control
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