Model-Based Nonlinear Control of a Low-Power Gas Turbine

Ailer, P.; Szederkényi, Gábor; Hangos, Katalin M.

doi:10.3182/20020721-6-es-1901.00224

Cited by 21 publications

(51 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, the structures of a conventional PID controller and a NARMA-L2 which is an ANN-based controller are briefly described. The relevant parameters are set up according to the requirements of the controller design for the Simulink model of a low-power gas turbine; already developed based on thermodynamic equations and energy balance (Ailer, Santa, Szederkenyi, & Hangos, 2002). A comparison is made between the performances of these controllers and concluding remarks are discussed.…”

Section: Black-box Modelsmentioning

confidence: 99%

“…In this study, the Simulink model was rebuilt using the same principles and equations. Eqn (1), (2) and (3) are the main equations of the gas turbine employed in the Simulink model (Ailer, Santa, Szederkenyi, & Hangos, 2002). Definition of each of the parameters in these equations is provided in Table 1.…”

Section: Gas Turbine Simulink Modelmentioning

confidence: 99%

“…Model verification was performed by open-loop simulations against qualitative operation experience and engineering intuition (Ailer, Santa, Szederkenyi, & Hangos, 2002). In this study, the Simulink model was rebuilt using the same principles and equations.…”

Section: Gas Turbine Simulink Modelmentioning

confidence: 99%

“…Ricketts (1997) showed that the dynamic model developed for a twin-shaft gas turbine by using a generic methodology and performance data sets, could represent an ideal application to adaptive control schemes. Ailer et al ( (2001), (2002), (2005)) carried out different research to design and develop control systems for a low-power gas turbine. Modifications in a heavy-duty power plant gas turbine control system were applied by Agüero et al (2002) .…”

Section: White-box Modelsmentioning

confidence: 99%

See 3 more Smart Citations

Design of conventional and neural network based controllers for a single-shaft gas turbine

Asgari

Jegarkandi

Chen

et al. 2017

AEAT

View full text Add to dashboard Cite

Purpose -The purpose of this paper is to develop and compare conventional and neural network based controllers for gas turbines.Design/methodology/approach -Design of two different controllers is considered. These controllers consist of a NARMA-L2 which is an ANN-based nonlinear autoregressive moving average (NARMA) controller with feedback linearization, and a conventional proportional-integrator-derivative (PID) controller for a low-power aero gas turbine.They are briefly described and their parameters are adjusted and tuned in Simulink-MATLAB environment according to the requirement of the gas turbine system and the control objectives. For this purpose, Simulink and neural network based modelling is employed. Performances of the controllers are explored and compared on the base of design criteria and performance indices.Findings -It is shown that NARMA-L2, as a neural network based controller, has a superior performance to the PID controller.Practical implications -Using artificial intelligence in gas turbine control systems.Originality/value -Providing a novel methodology for control of gas turbines.

show abstract

Section: Black-box Modelsmentioning

confidence: 99%

Section: Gas Turbine Simulink Modelmentioning

confidence: 99%

Section: Gas Turbine Simulink Modelmentioning

confidence: 99%

Section: White-box Modelsmentioning

confidence: 99%

See 2 more Smart Citations

Design of conventional and neural network based controllers for a single-shaft gas turbine

Asgari

Jegarkandi

Chen

et al. 2017

AEAT

View full text Add to dashboard Cite

show abstract

“…The total pressure p 3 * and temperature T 3 * upstream of the turbine can be considered as average values at the combustion chamber exit as suggested by Ailer, Sánta, Szederkényi and Hangos (2001). They represent the ability of the combustion chamber to conserve mass and internal energy of the flow.…”

Section: Governing Equations Of the State-space Representationmentioning

confidence: 99%

Linear Mathematical Model for State-Space Representation of Small Scale Turbojet Engine with Variable Exhaust Nozzle

Beneda

Andoga

Főző

2017

Period. Polytech. Transp. Eng.

View full text Add to dashboard Cite

show abstract

Nonlinear reference tracking control of a gas turbine with load torque estimation

Pongrácz

Ailer²,

Hangos

et al. 2007

Adaptive Control & Signal

Self Cite

View full text Add to dashboard Cite

Input-output linearization-based adaptive reference tracking control of a low-power gas turbine model is presented in this paper. The gas turbine is described by a third-order nonlinear input-affine state-space model, where the manipulable input is the fuel mass flowrate and the controlled output is the rotational speed. The stability of the one-dimensional zero dynamics of the controlled plant is investigated via phase diagrams. The input-output linearizing feedback is extended with a load torque estimator algorithm resulting in an adaptive feedback scheme. The tuning of controller parameters is performed considering three main design goals: appropriate settling time, robustness against environmental disturbances and model parameter uncertainties, and avoiding the saturation of the actuator. Simulations show that the closed-loop system is robust with respect to the variations in uncertain model and environmental parameters and its performance satisfies the defined requirements.

show abstract

Model-Based Nonlinear Control of a Low-Power Gas Turbine

Cited by 21 publications

References 5 publications

Design of conventional and neural network based controllers for a single-shaft gas turbine

Design of conventional and neural network based controllers for a single-shaft gas turbine

Linear Mathematical Model for State-Space Representation of Small Scale Turbojet Engine with Variable Exhaust Nozzle

Nonlinear reference tracking control of a gas turbine with load torque estimation

Contact Info

Product

Resources

About