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Citations
... Numerous simple static models exist in the literature [46] [47] [54] [55] [56], and [57], and it is shown that the model in Ref. [54] is superior to others. ...
This doctorate study aims to provide a methodology for developing aerodynamic and engine thrust models using simulated flight test data for the F16 fighter aircraft. An accurate and comprehensive representation of an aircraft's aerodynamic characteristics is required to design a flight control system or develop a high-fidelity flight simulator. Modern computational methods and wind tunnel testing can provide the aerodynamic database, but flight test data is required to obtain a more accurate and realistic aerodynamic database. As a result, system identification methods can characterize applied forces and moments acting on the aircraft. The F-16 nonlinear model also includes sensor models to simulate the actual flight data. The flight tests are carried out in the F16 simulation model using different excitations on the control surfaces. Simulation data is collected in predefined trim points. The equation error and output error methods are employed to analyze simulated data to estimate aerodynamic parameters in the time domain. The equation-error method is used firstly to identify aerodynamic parameters, and the results are then utilized as a starting point in the output-error process for fine-tuning. In general, thrust forces and moments are obtained from ground tests. The contribution of this doctoral study is to implement an iterative aerodynamic and thrust estimation approach in the absence of engine manufacturer data. The validation of resulting models is accomplished by comparing the measured flight data to the model’s predictions for identical control inputs, as specified by the Federal Aviation Administration (FAA).
... This model can be used in controller design, engine health monitoring, and sensor validation. Physics based modeling (white box model) approach has been widely used over many years in order to model gas turbine engines [1,2]. However, this approach can only be used when there is enough information about the physics of the system. ...
... NARX model is based on the linear autoregressive with exogenous inputs (ARX) model, which is commonly used in time-series modeling, and is used in many applications such as multistep ahead prediction and modeling of nonlinear dynamic systems. Equation (1) defines a NARX model and represents the relation between the model output and its input parameters [17] yðtÞ ¼ f ðyðt À 1Þ; …; yðt À n y Þ; uðt À n k Þ; …; uðt À n k À n u þ 1ÞÞ (1) where n y and n u are the lags of the output and input of the system, respectively. n k is the system input-output delay, and f is a nonlinear function. ...
Gas turbine is a complex system operating in non-stationary operation conditions for which traditional model-based modeling approaches have poor generalization capabilities. To address this, an investigation of a novel data-driven neural networks based model approach for a three-spool aero-derivative gas turbine engine (ADGTE) for power generation during its loading and unloading conditions is reported in this paper. For this purpose, a non-linear autoregressive network with exogenous inputs (NARX) is used to develop this model in MATLAB environment using operational closed-loop data collected from Siemens (SGT-A65) ADGTE. Inspired by the way biological neural networks process information and by their structure which changes depending on their function, multiple-input single-output (MISO) NARX models with different configurations were used to represent each of the ADGTE output parameters with the same input parameters. Usage of a single neural network to represent each of the system output parameters may not be able to provide an accurate prediction for unseen data and as a consequence, provides poor generalization. To overcome this problem, an ensemble of MISO NARX models is used to represent each output parameter. The major challenge of the ensemble generation is to decide how to combine results produced by the ensemble's components. In this paper, a novel hybrid dynamic weighting method (HDWM) is proposed. The simulation results show improvement in accuracy and robustness by using the proposed modeling approach.
... This model can be used in controller design, engine health monitoring and sensor validation. Physics based modelling (White box model) approach has been widely used over many years in order to model gas turbine engines [1,2]. However, this approach can only be used when there is enough information about the physics of the system. ...
Gas turbine is a complex system operating in non-stationary operation conditions for which traditional model-based modelling approaches have poor generalization capabilities. To address this, an investigation of a novel data driven neural networks based model approach for a three-spool aero-derivative gas turbine engine (ADGTE) for power generation during its loading and unloading conditions is reported in this paper. For this purpose, a non-linear autoregressive network with exogenous inputs (NARX) is used to develop this model in MATLAB environment using operational closed-loop data collected from Siemens (SGT-A65) ADGTE. Inspired by the way biological neural networks process information and by their structure which changes depending on their function, multiple-input single-output (MISO) NARX models with different configurations were used to represent each of the ADGTE output parameters with the same input parameters. First, data preprocessing and estimation of the order of these MISO models were performed. Next, a computer program code was developed to perform a comparative study and to select the best NARX model configuration, which can represent the system dynamics. Usage of a single neural network to represent each of the system output parameters may not be able to provide an accurate prediction for unseen data and as a consequence, provides poor generalization. To overcome this problem, an ensemble of MISO NARX models is used to represent each output parameter. The major challenge of the ensemble generation is to decide how to combine results produced by the ensemble’s components. In this paper, a novel hybrid dynamic weighting method (HDWM) is proposed. The verification of this method was performed by comparing its performance with three of the most popular basic methods for ensemble integration: basic ensemble method (BEM), median rule and dynamic weighting method (DWM). Finally, the generated ensembles of MISO NARX models for each output parameter were evaluated using unseen data (testing data). The simulation results based on datasets consisting for experimental data as well as data provided by Siemens high fidelity thermodynamic transient simulation program show improvement in accuracy and robustness by using the proposed modelling approach.
... Physics based models are based on first principles such as the law of physics, chemistry, etc (Nguyen 2000). This approach has been widely used over many years in order to model gas turbine engines (Bettocchi et al. 1996, Saleh 2017, Petkovic et al. 2019). However, this approach can only be used when there is enough information about the physics of the system. ...
To improve the anti-interference ability of engine afterburning control, the afterburning closed-loop control based on direct performance value as the controlled quantity has attracted a lot of research. Under the condition of afterburner fuel closed-loop control, the instability of the control system caused by the nonlinearity of the afterburner fuel actuator is more prominent. Traditional afterburning control system inevitably exhibits oscillation phenomenon in the nonlinearity intervals of the actuator. In this paper, the phenomenon of engine state oscillation caused by nonlinear characteristics of the afterburner fuel zonal supply system (FZSS) actuator is studied, and a compound control system based on neural network and μ modification control algorithm is proposed to eliminate the oscillation phenomenon. First, the mathematical model of the afterburner FZSS actuator is established on the Simulink platform to simulate the fuel flow discontinuity interval characteristics of the real afterburning system. Second, for the FZSS actuator combined with the mixed exhaust turbofan engine model, a direct performance control system named the compound μ correction adaptive control (CCAC) system is proposed with engine thrust as the controlled quantity to control the afterburner fuel flow in closed-loop way. The CCAC system contains multi μ modification controllers in the controller group module. If the FZSS actuator works in the fuel flow discontinuity intervals, the CCAC system can modify the engine thrust command and switch the controllers through the design of the controller switching strategy and the adaptive control law of each μ modification controller parameter, thus the nonlinear discontinuity intervals can be avoided to realize the smooth transition of turbofan engine states. Finally, the closed-loop numerical simulation is carried out for the designed control system. The simulation results show that the control system can effectively avoid the fuel flow discontinuity intervals and realize the smooth transition of the engine states in the whole operating range of the FZSS actuator. Meanwhile, the control system can improve the control effect adaptively for the engine with degraded performance.
