Design an Optimal T-s Fuzzy Pi Controller for a Non-inverting Buck-boost Converter
-
3217
Downloads
-
4331
Views
Authors
Omid Naghash Almasi
- Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
Vahid Fereshtehpoor
- Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
Abolfazl Zargari
- Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran.
Ehsan Banihashemi
- Department of Computer Science, Ferdows Branch, Islamic Azad University, Ferdows, Iran.
Abstract
In this paper, first, the different operation modes of a non–inverting buck–boost converter are examined, and then an optimal T-S fuzzy PI controller is proposed to control the converter under variable reference voltages. The controller is designed based on input-output pairs of the classic PI controller to employ both conscious and subconscious knowledge. For this aim, the initial fuzzy system generated by subtractive clustering method and then the Recursive Least Mean Square (RLS) is used to adjust the coefficients of consequent part of fuzzy rules. Simulation and experimental results show the superior control performance of the fuzzy PI controller over the classic PI controller.
Share and Cite
ISRP Style
Omid Naghash Almasi, Vahid Fereshtehpoor, Abolfazl Zargari, Ehsan Banihashemi, Design an Optimal T-s Fuzzy Pi Controller for a Non-inverting Buck-boost Converter, Journal of Mathematics and Computer Science, 11 (2014), no. 1, 42-52
AMA Style
Almasi Omid Naghash, Fereshtehpoor Vahid, Zargari Abolfazl, Banihashemi Ehsan, Design an Optimal T-s Fuzzy Pi Controller for a Non-inverting Buck-boost Converter. J Math Comput SCI-JM. (2014); 11(1):42-52
Chicago/Turabian Style
Almasi, Omid Naghash, Fereshtehpoor, Vahid, Zargari, Abolfazl, Banihashemi, Ehsan. "Design an Optimal T-s Fuzzy Pi Controller for a Non-inverting Buck-boost Converter." Journal of Mathematics and Computer Science, 11, no. 1 (2014): 42-52
Keywords
- Fuzzy PI controller
- Non–inverting Buck–boost Converter
- TSK fuzzy systems.
MSC
References
-
[1]
B. Sahu, G. A. Rincon-Mora, A Low Voltage, Dynamic, Non-inverting, Synchronous Buck-Boost Converter for Portable Applications, IEEE Trans. Power Electron. , 19 (2004), 443-452.
-
[2]
H. Xiao, S. Xie , Interleaving double-switch buck-boost converter, IET Power Electron, (2012), 899–908.
-
[3]
R. F. Coelho, F. M. Concer, D. C. Martins , Analytical and Experimental Analysis of DC-DC Converters in Photovoltaic Maximum Power Point Tracking Applications, In IECON 2010-36th Annual Conference on IEEE Industrial Electronics Society, (2010), 2778–2783.
-
[4]
V. Fereshtehpoor , Improvement in Power Factor Correction Capability in the Single Phase Non-inverting Buck-Boost Converter, Master’s science thesis, Dept. Electrical Eng., Science and Research Branch of Islamic Azad University, Tehran (2012)
-
[5]
Y. Lee, A. Khaligh, A. Emadi , A Compensation Technique for Smooth Transitions in a Non-inverting Buck–Boost Converter, IEEE Trans. Power Electron, 24 (2009), 1002–1015.
-
[6]
E. Schaltz, P. O. Rasmussen, A. Khaligh, Non-Inverting buck-boost converter for fuel cell applications, In Industrial Electronics, IECON 2008. 34th Annual Conference of IEEE, (2008), 855–860.
-
[7]
N. Mohan, T. M. Undeland, W. P. Robbins, Power Electronics Converters, Applications, and Design, J. Wiley, 3rd ed., (2003)
-
[8]
R. D. Middlebrook, S. R. Cuk , A general unified approach to modeling switching converter power stages, In Power Electronics Specialists Conference, 1 (1976), 18–34.
-
[9]
T. Takagi, M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans. Systems Man Cybernet, 15 (1985), 116–132.
-
[10]
W. L. Xin, A Course in Fuzzy Systems and Control, Englewood Cliffs, NJ: Prentice-Hall (1996)
-
[11]
S. Guillaume , Designing fuzzy inference systems from data: An interpretability-oriented review, IEEE Trans. Fuzzy Sys., 9 (2001), 426–443.
-
[12]
C. Hung, L. Huang, Extracting Rules from Optimal Clusters of Self-Organizing Maps, Int.Conf. on Computer Modeling and Simulation, 1 (2010), 382–386.
-
[13]
M. Setnes, Supervised fuzzy clustering for rule extraction, IEEE Trans. fuzzy sys. , 8 (2000), 416–424.
-
[14]
A. Priyono, M. Ridwan, A. J. Alias, R. A. OK Rahmat, A. Hassan, M. A. Mohd Ali, Generation of fuzzy rules with subtractive clustering, Journal Technology, 43 (2012), 143–153.
-
[15]
C. Restrepo, J. Calvente, A. Cid-Pastor, A. E. Aroudi, R. Giral, A Noninverting Buck–Boost DC–DC Switching Converter With High Efficiency and Wide Bandwidth, IEEE Trans. Power Electron, 26 (2011), 2490–2503.
-
[16]
H. K. Lam, S.-C Tan, Stability analysis of fuzzy-model-based control systems: application on regulation of switching DC-DC converter, IET Control Theory & Applications, 3 (2009), 1093–1106.
-
[17]
R. Erickson, D. Maksimovic, Fundamental of power electronics, Springer, 2nd ed. (2000)
-
[18]
J. J. Buckley, Sugeno type controllers are universal controllers, Fuzzy Sets and Systems, 53 (1993), 299–303.
-
[19]
R. Qi, M. A. Brdys, Stable indirect adaptive control based on discrete-time T–S fuzzy model, FuzzySets and Systems, 159 (2008), 900–925.
-
[20]
S. Chiu, Extracting fuzzy rules from data for function approximation and pattern classification, Fuzzy Information Engineering: A Guided Tour of Application. D. Dubois, H. Prade and R. Yager(eds), John Wiley Sons (1997)
-
[21]
K. Ogata, Modern control engineering, Prentice Hall, 5th ed. (2010)