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Inicio Revista Iberoamericana de Automática e Informática Industrial RIAI Estudio comparativo de algoritmos de auto-ajuste de controladores PID. Resultado...
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Vol. 9. Núm. 2.
Páginas 182-193 (abril - junio 2012)
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6567
Vol. 9. Núm. 2.
Páginas 182-193 (abril - junio 2012)
Open Access
Estudio comparativo de algoritmos de auto-ajuste de controladores PID. Resultados del Benchmark 2010-2011 del Grupo de Ingeniería de Control de CEA
Comparative Study of Auto-tuning Algorithms for PID Controllers. Results of the 2010-2011 Match of the Control Engineering Group of CEA
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6567
J.A. Romero-Péreza,
Autor para correspondencia
romeroj@uji.es

Autor para correspondencia.
, O. Arrietab,c, F. Padulad, G. Reynoso-Mezae, S. Garcia-Nietoe, P. Balaguera
a Departamento de Ingeniería de Sistemas Industriales y Diseño. Universidad Jaume I Campus del Riu Sec, E-12080 Castelló de la Plana, España
b Departament de Telecomunicació i d’Enginyeria de Sistemes. Universitat Autònoma de Barcelona 08193 Bellaterra, Barcelona, España
c Departamento de Automática. Escuela de Ingeniería Eléctrica. Universidad de Costa Rica 11501-2060 San José, Costa Rica
d Dipartimento di Ingegneria dell’Informazione. Università degli Studi di Brescia Via Branze 38, 25213 Brescia, Italia
e Instituto de Automática e Informática Industrial. Universidad Politécnica de Valencia Edificio 8G - Acceso D - Planta 3. Camino de Vera, s/n, 46022 Valencia, España
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En este artículo se comparan tres métodos de auto-ajuste de controladores PID que consideran diferentes tipos de experimentos para obtener información de la dinámica del proceso y distintos métodos de cálculo de los parámetros del controlador para minimizar el efecto de las perturbaciones. Los métodos fueron presentados en el concurso anual organizado por el grupo de Ingeniería de Control de CEA-IFAC del curso 2010-2011. Para la comparación se aplica la metodología de evaluación de algoritmos de autoajuste que tiene en cuenta tanto la fase de experimento como las prestaciones que se consiguen en la fase de control.

Palabras clave:
PID
auto-ajuste
rechazo de perturbaciones
Abstract

In this paper three PID auto-tuning algorithms which are mainly focused on the disturbance rejection problem are compared. The algorithms differ in both the experiments carried out to obtain information of the process dynamic and the methods for calculating the controller parameters. The algorithms were presented in the 2010-2011 Match of the Control Engineering Group of CEA. The comparison is based on an evaluation methodology that takes into account the experimental phase as well as the closed loop performance during the control phase.

Keywords:
PID
auto-tuning
disturbance rejection
Referencias
[Alfaro, 2006]
V.M. Alfaro.
Low-order models identification from process reaction curve.
Ciencia y Tecnología (Costa Rica), 24 (2006), pp. 197-216
[Åström and Hägglund, 2006]
K. Åström, T. Hägglund.
Advanced PID Control. ISA - The Instrumentation.
Systems, and Automation Society, (2006),
[Åström et al., 1998]
K. Åström, H. Panagopoulos, T. Hägglund.
Design of PI controllers based on non-convex optimization.
Automatica, 34 (1998), pp. 585-601
[Åström and Hägglund, 1984]
K.J. Åström, T. Hägglund.
Automatic tuning of simple regulators with specifications on phase and amplitude margins.
Automatica, 20 (1984), pp. 645-651
[Fleming and Purshouse, 2002]
P. Fleming, R. Purshouse.
Evolutionary algorithms in control systems engineering: a survey.
Control Engineering Practice, 10 (2002), pp. 1223-1241
[Greg Baker, 2009]
Greg Baker, W., January 2009. Is automated PID tuning dependable? Avilable on-line at http://www.controleng.com/index.php?id=483&cHash=081010&tx_ttnews[tt_news]=12682.
[Hang et al., 2002]
C. Hang, K. Åström, Q. Wang.
Relay feedback auto-tuning of process controllers-a tutorial review.
Journal of Process Control, 12 (2002), pp. 143-162
[Herreros et al., 2002]
A. Herreros, E. Baeyens, J.R. Perán.
Design of pid-type controllers using multiobjective genetic algorithms.
ISA Transactions, 41 (2002), pp. 457-472
[Iruthayarajan and Baskar, 2009]
M.W Iruthayarajan, S. Baskar.
Evolutionary algorithms based design of multivariable pid controller.
Expert Systems with applications, 36 (2009), pp. 9159-9167
[Iruthayarajan and Baskar, 2010]
M.W. Iruthayarajan, S. Baskar.
Covariance matrix adaptation evolution strategy based design of centralized pid controller.
Expert Systems with Applications, 37 (2010), pp. 5775-5781
[Kim et al., 2008]
T.-H. Kim, I. Maruta, T. Sugie.
Robust PID controller tuning based on the constrained particle swarm optimization.
Automatica, 44 (2008), pp. 1104-1110
[Nobakhti and Wang, 2008]
A. Nobakhti, H. Wang.
A simple self-adaptive differential evolution algorithm with application on the alstom gasifier.
Applied soft computing, 8 (2008), pp. 350-370
[Padula and Visioli, 2010]
Padula, F., Visioli, A., 2010. Tuning of fractional PID controllers for integral processes. In: Proceedings of FDA’10. The 4th IFAC Workshop Fractional Di_erentiation and its Applications. Badajoz, Spain.
[Padula and Visioli, 2011]
F. Padula, A. Visioli.
Tuning rules for optimal PID and fractional-order PID controllers.
Journal of Process Control, 21 (2011), pp. 69-81
[Panagopoulos et al., 2002]
H. Panagopoulos, K. Åström, T. Hägglund.
Design of PID controllers based on constrained optimisation.
IEE Proceedings Control Theory & Applications, 149 (2002), pp. 32-40
[Price, 1999]
Price, K.V., 1999. An introduction to di_erential evolution. McGraw-Hill Ltd., UK, Maidenhead, UK, England, pp. 79-108.
[Reynoso-Meza et al., 2011a]
Reynoso-Meza, G., Blasco, X., Sanchis, J., García-Nieto, S., September 2011a. Auto-ajuste evolutivo de controladores PID. In: de Automática, C.E. (Ed.), Memorias de las XXXII Jornadas de Automática.
[Reynoso-Meza et al., 2011b]
Reynoso-Meza G., Sanchis J., Blasco X., Herrero J.M., 2011b. Handling control engineering preferences: How to get the most of pi controllers. In: Proceedings of 16th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA2011), September 5-9, Toulouse-France.
[Reynoso-Meza et al., 2011c]
Reynoso-Meza, G., Sanchis, J., Blasco, X., Martínez, M., April 2011c. An empirical study on parameter selection for multiobjective optimization algorithms using di_erential evolution. In: Proceedings of IEEE Symposium on Di_erential Evolution (SDE2011).
[Romero and Sanchis, 2011]
J. Romero, R. Sanchis.
Benchmark para la evaluación de algoritmos de auto-ajuste de controladores PID.
Revista Iberoamericana de Automática de Informática Industrial, 8 (2011), pp. 112-117
[Romero et al., 2011]
J.-A. Romero, R. Sanchis, P. Balaguer.
PI and PID auto-tuning procedure based on simplified single parameter optimization.
Journal of Process Control, 21 (2011), pp. 840-851
[Sanchis et al., 2010]
R. Sanchis, J. Romero, P. Balaguer.
Tuning of PID controllers based on simplified single parameter optimization.
International Journal of Control, 83 (2010), pp. 1785-1798
[Storn, 2008]
R. Storn.
Differential Evolution Research - Trends and Open Questions.
Springer-Verlag, (2008),
[Storn and Price, 1997]
R. Storn, K. Price.
Differential evolution: A simple and effcient heuristic for global optimization over continuous spaces.
Journal of Global Optimization, 11 (1997), pp. 341-359
[Tan et al., 2005]
Tan, K., Lee, T., Ferdous, R., 2005. Springer, Ch. Automatic PID Controller Tunning-The Nonparametric Approach, pp. 147-182.
[Tavakoli et al., 2007]
S. Tavakoli, I. Gri_n, P.J. Fleming.
Multi-objective optimization approach to the PI tuning problem.
In: Proceedings of the IEEE congress on evolutionary computation (CEC2007)., (2007), pp. 3165-3171
[Wang et al., 1997]
Q.-G. Wang, C.-C. Hang, B. Zou.
Low-order modeling from relay feedback.
Industrial & Engineering Chemistry Research, 36 (1997), pp. 375-381
[Xue et al., 2010]
Y. Xue, D. Li, F. Gao.
Multi-objective optimization and selection for the PI control of ALSTOM gasifier problem.
Control Engineering Practice, 18 (2010), pp. 67-76
[Zhao et al., 2011]
S.-Z. Zhao, M.W. Iruthayarajan, S. Baskar, P. Suganthan.
Multiobjective robust pid controller tuning using two lbests multi-objective particle swarm optimization.
Information Sciences, 181 (2011), pp. 3323-3335
[Ziegler and Nichols, 1942]
J. Ziegler, N. Nichols.
Optimum Settings for Automatic Controllers.
ASME Transactions, (1942), pp. 759-768
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