Identifying linear models of systems suffering nonlinear distortions, with a gas turbine application

Evans, D.C.; Rees, D.; Jones, David Lee

doi:10.1049/ip-cta:19951841

Cited by 35 publications

(8 citation statements)

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“…A signal such as this, composed of only odd-harmonics, is immune to even-order nonlinear effects and remains amenable to CF minimisation (see Evans et at, 1995). The CF was minimised using the Guillaume approach and the resulting signal is shown in the time and frequency domains in Fig.…”

Section: F U(t) = Ag Cos (I E 21e4mentioning

confidence: 99%

Testing and Modelling Gas Turbines Using Multisine Signals and Frequency-Domain Techniques

Evans

Borrell

Rees

1998

Volume 5: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation;

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The frequency-domain identification of gas turbine dynamics is discussed. Models are directly estimated from engine data and used to validate linearised thermodynamic models derived from the engine physics. This work is motivated by the problems previously • encountered when using time-domain methods. A brief overview of frequency-domain techniques is presented and the design of appropriate multisine test signals is discussed. Practical results are presented for the modelling of the fuel feed to shaft speed dynamics of a twin-spool engine. The gathered data are analysed and the frequency response functions of the engine are estimated. The identification of parametric s-domain models is discussed in detail and a comparison made between the identified models and the linearised thermodynamic models. The influence of engine nonlinearities on the linear models is also examined.

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Section: F U(t) = Ag Cos (I E 21e4mentioning

confidence: 99%

Testing and Modelling Gas Turbines Using Multisine Signals and Frequency-Domain Techniques

Evans

Borrell

Rees

1998

Volume 5: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation;

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“…Recent work by Evans et al [2][3][4][5] concentrated on testing the engine using small-amplitude multisine signals and then using frequency-domain techniques to identify linear models of high accuracy. The errors due to noise and nonlinearities were assessed and found to be small for these small-signal models.…”

Section: Introductionmentioning

confidence: 99%

Global Nonlinear Modelling of Gas Turbine Dynamics Using NARMAX Structures

Chiras

Evans

Rees

2001

Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation;

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This paper examines the estimation of a global nonlinear gas turbine model using NARMAX techniques. Linear models estimated on small-signal data are first examined and the need for a global nonlinear model is established. A nonparametric analysis of the engine nonlinearity is then performed in the time and frequency domains. The information obtained from the linear modelling and nonlinear analysis is used to restrict the search space for nonlinear modelling. The nonlinear model is then validated using large-signal data and its superior performance illustrated by comparison with a linear model. This paper illustrates how periodic test signals, frequency domain analysis and identification techniques, and time-domain NARMAX modelling can be effectively combined to enhance the modelling of an aircraft gas turbine.

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“…In particular, the high gain input direction is whereas the low gain input direction is . It is worth noting that while the system is ill-conditioned, it is not highly interactive since the relative gain array at steady-state is (13) where denotes the Schur product.…”

Section: A Description Of Process and Conditions For Simulationmentioning

confidence: 99%

Design of Ternary Signals for MIMO Identification in the Presence of Noise and Nonlinear Distortion

Tan

Godfrey

Barker

2009

IEEE Trans. Contr. Syst. Technol.

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Identifying linear models of systems suffering nonlinear distortions, with a gas turbine application

Cited by 35 publications

References 0 publications

Testing and Modelling Gas Turbines Using Multisine Signals and Frequency-Domain Techniques

Testing and Modelling Gas Turbines Using Multisine Signals and Frequency-Domain Techniques

Global Nonlinear Modelling of Gas Turbine Dynamics Using NARMAX Structures

Design of Ternary Signals for MIMO Identification in the Presence of Noise and Nonlinear Distortion

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