Fault detection in wheeled mobile robot based on extended kalman filter

Jouili, A.; Boussaid, Boumedyen; Zouinkhi, Ahmed; Abdelkrim, Mohamed Naceur

doi:10.1109/sta56120.2022.10019207

Cited by 2 publications

(2 citation statements)

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“…Additionally, [12] introduces a Kalman filter designed for joint state prediction and unknown input estimation within linear stochastic discrete-time systems subject to intermittent unknown inputs in measurements. Interests in FDI for nonlinear systems have grown significantly in recent years due to the fact that most of the systems, we face in practice, are nonlinear in nature such as [13] where the FDI system is based on a single model EKF filter that generates residuals as soon as the behavior of the aircraft deviates from expected, also [14] directs its focus towards fault detection in wheeled mobile robots utilizing an EKF filter. The fault detection process typically involves two primary steps: residual generation and subsequent residual evaluation.…”

Section: Of 21mentioning

confidence: 99%

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Fault Detection of Multi Wheeled Robot Consensus Based on EKF

JOUILI,

Boussaid,

Zouinkhi

et al. 2024

Preprint

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In this article the problem of detection and isolation (FDI) in wheeled mobile robot is 1 treated. first of all we consider a master-slave robot system in which the master robot has to follow a 2 desired trajectory given by a well-determined control law, then the slave is controlled by the master. 3 However in real environment there is no ideality because faults can appear in the master or slave 4 or even the both and affect the system and may lead to unacceptable results so to ensure a well 5 functioning an extended kalman filter is tuned to diagnosis eventual faults and to generate residuals 6 in order to detect and isolate them. The performance of an estimator based on an EKF is simulated 7 based MATLAB Simulink simulations.

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Section: Of 21mentioning

confidence: 99%

“…Consequently, the Kalman equations will exhibit greater stability, as any minor deviations in the positive definite nature of the covariance matrices will be corrected in the subsequent iteration. According to (14) :…”

Section: Hypothesismentioning

confidence: 99%

Fault Detection of Multi Wheeled Robot Consensus Based on EKF

JOUILI,

Boussaid,

Zouinkhi

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Fault Detection of Multi-Wheeled Robot Consensus Based on EKF

Jouili,

Boussaid,

Zouinkhi

et al. 2024

Actuators

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Synchronizing a network of robots in consensus is an important task for cooperative work. Detecting faults in a network of robots in consensus is a much more important task. In considering a formation of Wheeled Mobile Robots (WMRs) in a master–slave architecture modeled by graph theory, the main objective of this study was to detect and isolate a fault that appears on a robot of this formation in order to remove it from the formation and continue the execution of the assigned task. In this context, we exploit the extended Kalman filter (EKF) to estimate the state of each robot, generate a residual, and deduce whether a fault exists. The implementation of this technique was proven using a Matlab simulator.

show abstract

Fault detection in wheeled mobile robot based on extended kalman filter

Cited by 2 publications

References 13 publications

Fault Detection of Multi Wheeled Robot Consensus Based on EKF

Fault Detection of Multi Wheeled Robot Consensus Based on EKF

Fault Detection of Multi-Wheeled Robot Consensus Based on EKF

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