Controller Design for the Twin Rotor MIMO System via Reduced-Order Modelling

Chandra, Gauri; Mathew, Lini; Negi, Richa

doi:10.1109/iceca.2018.8474547

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…If the reduced system possesses the same characteristics as that of higher-order system, then the reduced-order system can be used to design the suitable LFC. 23 If the model of the higher-order system is simplified too much, then it may lead to a wrong conclusion, whereas less reduced order leads to the complexities. So, a trade-off between the two conditions must be taken care of to get the efficient LFC design.…”

Section: Introductionmentioning

confidence: 99%

Designing of 2‐degree of freedom load frequency controller for power system using novel improved pole clustering and genetic method of reduced‐order modelling

Gupta

Manocha

2021

Int Trans Electr Energ Syst

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Section: Introductionmentioning

confidence: 99%

Designing of 2‐degree of freedom load frequency controller for power system using novel improved pole clustering and genetic method of reduced‐order modelling

Gupta

Manocha

2021

Int Trans Electr Energ Syst

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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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Controller Design for the Twin Rotor MIMO System via Reduced-Order Modelling

Cited by 2 publications

References 9 publications

Designing of 2‐degree of freedom load frequency controller for power system using novel improved pole clustering and genetic method of reduced‐order modelling

Designing of 2‐degree of freedom load frequency controller for power system using novel improved pole clustering and genetic method of reduced‐order modelling

Subspace identification of fault modes for a twin-rotor system

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