Performance Evaluation of a PI Neuro-Fuzzy controller for a Turbogas Unit
DOI:
https://doi.org/10.46842/ipn.cien.v24n1a05Keywords:
neuro-fuzzy system, neuro-fuzzy control, digital control, analisys of performanceAbstract
Gas turbines are used as primary impellers in the generation of electrical energy. The performance of a turbo gas unit is dependent on the control unit that it has, it is significant in optimization in the system execution. This paper shows the results of the evaluation of robustness in the performance of a model of a neuro -fuzzy controller for a turbogas unit, it is a first step for application in the real process. The design of the neuro-fuzzy controller is based on a digital PI controller of the speed type. The analysis and evaluation of the controller are done by simulations in discrete time with a first order system with delay. The tests include variations of the process parameters: gain, delay and time constant. The effect of deterministic and stochastic disturbances on the control signal, the manipulated variable and the controlled variable is evaluated. The results obtained demonstrate the feasibility of using a neuro-fuzzy controller, integrated in digital equipment, for real applications.
References
A. Giampaolo, Gas turbine handbook: principles and practices, The Fairmont Press, 3ª ed., Londres, 2006.
G. Rogers, H. Saravanamutto, Gas turbine theory. Longman House, 4ª ed., Londres, 1996.
General Electric, Turbina de gas (01), 2019. Recuperado de https://www.ge.com/power/gas/gas-turbines
R. Garduño, M. Sánchez, "Control System Modernization: Turbogás Unit Case Study," IFAC Symposium on Control of Power Plants and Power Systems, vol. 2, pp. 245-250, Cancún, México 1995.
R. Garduño, G. Madrigal, M. Sánchez, "Modernización de los Sistemas de Control en la Central Termoeléctrica de Ciclo Combinado Gómez Palacio, parte III: Turbinas de Gas". Boletín IIE, vol. 20, no. 3, pp. 117-125, mayo-junio 1996.
J. Reason, "Why High Performance Controls are Vital for Gas Turbines," Electrical World, pp. 71-74, abril 1989.
N. Hadroug, A. Hafaifa, M. Guemana, "Heavy duty gas turbine monitoring based on adaptive neuro-fuzzy inference system: speed and exhaust temperature control", Mathematics-in-Industry Case Studies, vol.8, no.8, 2017, https://doi.org/10.1186/s40929-017-0017-8
A. Rodriguez-Martinez, R. Garduno-Ramirez, L. G. Vela-Valdes, "PI Fuzzy Gain-Scheduling Speed Control at Startup of a Gas-Turbine Power Plant", IEEE Transactions On Energy Conversion, vol. 26, no. 1, 2011.
S. De Lara, R. Garduño, M. Sánchez, L. Castelo, M. Carretero, "A Process Knowledge-Based Controller for Maneuverability Improvement of a Nonlinear Industrial Process," Springer , vol. 25-27, noviembre 2002.
C. D. García, "Control Digital de Unidades Turbogás", Tesis de Maestría, Centro Nacional de Investigación y Desarrollo Tecnológico, México, 1997.
C. D. García, R. Garduño, "Gas Turbine Fuzzy Speed Control", 2nd Joint Mexico-USA International Conference on Neural Networks and Neurocontrol, Sianka'an, Mexico 1997.
C. D. García, R. Garduño, "Control Software System of a Turbogás Power Unit", 5th IFAC Workshop on Algorithms and Architectures for Real Time Control, pp. 131-136, Cancún, México, 1998.
M. Sánchez, L. Bahamaca, "Realización de controladores lógicos difusos para el control de procesos en tiempo real: especificación y diseño", 2º Encuentro Nacional de Computación, Pachuca, México,1999.
M. Sánchez, "Control for Gas Turbines", 1st Annual ISA POWID/EPRI/DOE Joint Controls and Instrumentation Conference, San Antonio, USA 2000.
M. Pat, S. de Lara, "Sintonización con Redes Neuronales de un Controlador PID. Aplicación a una unidad turbogás", Información Tecnológica, vol. 10, no. 6, pp. 25-32, 1999.
S. De Lara, M. A. Martínez," Desarrollo del Sistema para la Sintonización de Controladores Difusos Usando Redes Neuronales Artificiales," IIE reporte interno: 11500INDT (A5), enero-marzo 1999.
J.S.R Jang, N. Gulley, Fuzzy Logic Toolbox, Natick, MS, Mathworks 2014.
J. Ramírez, M. Chacón, "Redes neuronales para el procesamiento de imágenes, una revisión de la última década", RIEE&C, vol. 9, no. 1, 2011.
P. Ponce, Inteligencia Artificial con Aplicaciones a la Ingeniería, Alfaomega, 2010.
Downloads
Published
Issue
Section
License
Copyright (c) 2020 Instituto Politecnico Nacional
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
