Kalman Filter Based State Estimation for Linearized Twin Rotor System

Haider, Khawaja Shafiq; Kazmi, I. H.; Rehman, Maria

doi:10.1109/fit.2011.40

Cited by 8 publications

(2 citation statements)

References 14 publications

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“…However, a drawback of this approach is that it requires process inputs to be persistently exciting. This constraint is inadequate for ill conditioned multivariable processes because in this case model order can be underestimated, leading to subsequent identification of poor models (Misra and Nikolaou, 2003;Haider et al, 2011;Musoff and Zarchan, 2009;DeBitetto, 1989;Ehrman and Lanterman, 2008;Palmer et al, 1996;Woo-han et al, 2006;Armenta et al, 2017;Chandra et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Subspace identification of fault modes for a twin-rotor system

Haider

Huda

Rasool³

et al. 2020

IJIUS

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PurposeThe purpose of this paper is to identify the fault modes of a nonlinear twin-rotor system (TRS) using the subspace technique to facilitate fault identification, diagnosis and control applications.Design/methodology/approachFor identification of fault modes, three types of system malfunctions are introduced. First malfunction resembles actuator, second internal system dynamics and third represents sensor malfunction or offset. For each fault scenario, the resulting TRS model is applied with persistently exciting inputs and corresponding outputs are recorded. The collected input–output data are invoked in NS4SID subspace system identification algorithm to obtain the unknown fault model. The identified actuator fault modes of the TRS can be used for fault diagnostics, fault isolation or fault correction applications.FindingsThe identified models obtained through system identification are validated for correctness by comparing the response of the actual model under the fault condition and identified model. The results certify that the identified fault modes correctly resemble the respective fault conditions in the actual system.Originality/valueThe utilization of proposed work for current research emphasized the area of fault detection, diagnosis and correction applications that makes its value significantly. These modes when used for diagnosis purposes allow users to timely get intimated and rectify the performance degradation of the plant before it gets totally malfunctioned. Moreover, the slight performance degradation is also indicated when fault diagnosis is performed.

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Section: Introductionmentioning

confidence: 99%

Subspace identification of fault modes for a twin-rotor system

Haider

Huda

Rasool³

et al. 2020

IJIUS

Self Cite

View full text Add to dashboard Cite

show abstract

“…El trabajo realizado en [21] analiza el comportamiento de dos propuestas de filtro Kalman para estimar los estados de una suspensión convencional, donde la diferencia entre las dos es la inclusión de la señal de perturbación en la superficie de desplazamiento, encontrando que la propuesta sin la señal de perturbación no estima de manera adecuada los estados del sistema, por otra parte la inclusión de dicha información en la segunda propuesta hace que los estados se estimen de manera adecuada. En el desarrollo de este trabajo se realizaron las dos propuestas obteniendo resultados similares, por lo cual se incluyo dentro del diseño del filtro Kalman la señal de perturbación en la superficie de desplazamiento.…”

Section: Señales De Los Sensoresunclassified