Ceri Evans

Bangor University

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 obtaine...

This paper examines the minimization of the signal crest factor using a frequency-domain method. This method is based on the observation that low crest factor signals possess properties that reduce the effect of system nonlinearities. The main idea of this method is that instead of setting the signal crest factor as the cost function to be minimize...

New insights on the frequency-domain output properties of nonlinear systems driven by multiharmonic signals will be discussed in this paper. These are based on a detailed analysis of the mechanisms at work on the generation of a class of nonlinear distortions, termed harmonic components. This leads to the derivation of formulae to calculate the num...

When measuring the best linear approximation of systems suffering from nonlinear distortions a specific class of periodic multiharmonic signals is normally used. These are signals with uniformly distributed random phases, termed random phase multisines. In this paper, it is shown that measurements of the best linear approximation of nonlinear syste...

This paper presents controllers based on linear and nonlinear models of an aircraft gas turbine engine. These models along with the performance indexes, ITAE, IAE and IES are used to estimate the parameters of a PID controller. The parameters and hence the quality of the controllers are very much dependent on the accuracy of the models. It is shown...

In this paper the orthogonal estimation algorithm is used to estimate a NARMAX model for an aircraft gas turbine. The performance of the model is validated using a range of small and large signal tests and by examining the model's static and dynamic characteristics. The NARMAX representation allows the direct mapping to the frequency domain by comp...

In this paper a feedforward neural network is used to model the fuel flow to shaft speed relationship of a Spey gas turbine engine. The performance of the estimated model is validated against a range of small and large signal engine tests. It is shown that the performance of the estimated models is superior to that of the estimated linear models.

The estimation of a nonlinear autoregressive moving average with exogenous inputs (NARMAX) model of an aircraft gas turbine is presented. A method is proposed whereby periodic signals with certain harmonic content are used to qualify the nature of the nonlinearity of the engine in the frequency domain. The static behavior of the engine is investiga...

In this paper the orthogonal estimation algorithm is used to estimate a NARMAX model for an aircraft gas turbine. The performance of the model is validated using a range of small and large signal tests and by examining the model's static and dynamic characteristics. The NARMAX representation allows the direct mapping to the frequency domain by comp...

The linear multivariable modelling of an aircraft gas turbine is presented. A frequency-domain identification method is employed to estimate a family of models from engine data at a range of operating points. It is found that the fuel feed to shaft speed dynamics can be represented by second-order models. This matches the results obtained for the r...

This paper examines the effects of nonlinearities on frequency response function measurements using periodic multifrequency signals. A class of broadband pilot test signals is proposed, termed sparse odd multisines, which can be used to establish the system bandwidth and detect nonlinearities. Signals are then defined within this class which allow...

For Pt. I see ibid. vol. 49, pp. 602-609, 2000. This paper examines the effects of nonlinear distortions on frequency response functions estimated using multisine test signals. The aim is to minimize the distortion introduced by the nonlinearity, for a given input power constraint. A number of different multisine signals are compared for this purpo...

This paper describes the estimation of parametric and nonparametric models of the fuel feed to shaft speed dynamics of a twin-shaft gas turbine engine, using frequency-domain techniques. Data gathered from practical testing of the turbine are presented and shown to be of high quality. Accurate models are then estimated at several points along the t...

The identification of the fuel flow to shaft speed dynamics of a twin-shaft gas turbine is addressed, with the aim of validating thermodynamic engine models. A measured input signal must be used in estimation in order to exclude the fuel feed dynamics from the model. This has been shown to present problems when fitting discrete models to engine dat...

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 i...

The frequency-domain measurement of the Volterra kernels of a nonlinear system using periodic multisine signals is now a practical possibility. An analysis is presented of the harmonic output of a Volterra kernel when excited with a multiharmonic signal, which lays the basis for the design of such signals. This is followed by a review of previous w...

Identification of the fuel flow to shaft speed dynamics of a gas turbine is examined. Poor quality time domain models are obtained. This is shown to be a result of using a measured input signal for estimation, in order to exclude the actuator dynamics. This violates the underlying assumption of time domain estimation that the input signal is piece-...

The identification of the fuel flow to shaft speed dynamics of a two shaft gas turbine engine is addressed. The measurement problem is discussed along with the limitations of previous work. The paper discusses why a measured input signal must be used for identification and why poor time domain models are consequently obtained, caused by the violati...

In this paper a parameter estimation algorithm is used to estimate a Wiener model for an aircraft gas turbine. The performance of the model is validated using a range of small and large signal tests and by examining the model's static and dynamic characteristics.