Experimental Test of an Interacting Multiple Model Filtering Algorithm for Actuator Fault Detection and Diagnosis of an Unmanned Quadrotor Helicopter

2012 ◽  
pp. 473-482 ◽  
Author(s):  
Mohammad Hadi Amoozgar ◽  
Abbas Chamseddine ◽  
Youmin M. Zhang
Keyword(s):  
Fault Detection ◽  
Experimental Test ◽  
Fault Detection And Diagnosis ◽  
Interacting Multiple Model ◽  
Actuator Fault ◽  
Multiple Model ◽  
Filtering Algorithm ◽  
Unmanned Quadrotor Helicopter ◽  
Quadrotor Helicopter ◽  
Detection And Diagnosis

Sensor Fault Detection and Diagnosis in Dead Reckoning System of Mobile Robot: Interacting Multiple-Model Approach

2002 ◽  
Vol 14 (4) ◽  
pp. 342-348
Author(s):  
Masafumi Hashimoto ◽  
◽  
Hiroyuki Kawashima ◽  
Fuminori Oba ◽  
Keyword(s):  
Fault Detection ◽  
Mobile Robot ◽  
Failure Modes ◽  
Dead Reckoning ◽  
Fault Detection And Diagnosis ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Sensor Fault ◽  
Sensor Fault Detection ◽  
Detection And Diagnosis

An interacting multiple-model (IMM) approach to sensor fault detection and diagnosis (FDD) in dead reckoning is proposed for navigating mobile robots. In this approach, changes of sensor normal/failure modes are explicitly modeled as switching from one mode to another in a probabilistic manner, and the sensor FDD and state estimate are achieved via a bank of parallel Kalman filters. To provide better FDD performance, mode probability averaging and heuristic decisionmaking logic are combined with the IMM based FDD algorithm. The proposed FDD is implemented on a skid-steered mobile robot, where 32 system modes (one normal mode and 31 hard sensor failure modes) of 5 sensors (4 wheel-encoders and one yaw-rate gyro) are handled. Experimental results validate the effectiveness of the proposed FDD.

Application of interacting multiple model-based fault detection method on a hydraulic two-tank system

2018 ◽  
Vol 8 (2) ◽  
pp. 42-51
Author(s):  
M Hajizadeh ◽  
M G Lipsett
Keyword(s):  
Fault Detection ◽  
Confusion Matrix ◽  
Detection Algorithm ◽  
Fault Detection And Diagnosis ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Non Linear ◽  
Tank System ◽  
Efficient Scheme ◽  
Estimation Scheme

This paper addresses the problem of designing a fault identification and detection algorithm for non-linear systems. Timely identification and detection of a fault in a system is crucial in condition monitoring systems. However, finding the source of the failure is not trivial in systems with large numbers of components and complex component relationships. In this paper, an efficient scheme to detect adverse changes in system reliability and find the failed component is proposed, based on the interacting multiple model (IMM) algorithm, with fault detection and diagnosis formulated as a hybrid multiple model estimation scheme. The proposed approach provides an integrated framework for fault detection, diagnosis and state estimation. Its performance is illustrated for fault detection of a non-linear two-tank system. The proposed method can be used with different kinds of filters, using the confusion matrix and classification accuracy as comparison metrics. A particle filter is used with the IMM algorithm and its performance is compared to the linear Kalman filter as a comparative case concerning the improvement that can be achieved when going beyond the consideration that the system is linear.

scholarly journals Actuator fault detection and isolation on a quadrotor unmanned aerial vehicle modeled as a linear parameter-varying system

2019 ◽  
Vol 52 (9-10) ◽  
pp. 1228-1239 ◽  
Author(s):  
Julio Alberto Guzmán-Rabasa ◽  
Francisco Ronay López-Estrada ◽  
Brian Manuel González-Contreras ◽  
Guillermo Valencia-Palomo ◽  
Mohammed Chadli ◽  
...  
Keyword(s):  
Fault Detection ◽  
Unmanned Aerial Vehicle ◽  
Fault Detection And Diagnosis ◽  
Fault Detection And Isolation ◽  
Actuator Fault ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Aerial Vehicle ◽  
Parameter Varying ◽  
Detection And Diagnosis

This paper presents the design of a fault detection and diagnosis system for a quadrotor unmanned aerial vehicle under partial or total actuator fault. In order to control the quadrotor, the dynamic system is divided in two subsystems driven by the translational and the rotational dynamics, where the rotational subsystem is based on a linear parameter-varying model. A robust linear parameter-varying observer applied to the rotational subsystem is considered to detect actuator faults, which can occur as total failures (loss of a propeller or a motor) or partial faults (degradation). Furthermore, fault diagnosis is done by analyzing the displacements of the roll and pitch angles. Numerical experiments are carried out in order to illustrate the effectiveness of the proposed methodology.

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