Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Allouche, Moeza; * | Dahech, Karima | Chaabane, Mohameda | Mehdi, Drissb
Affiliations: [a] Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (Lab-STA), National School of Engineering of Sfax, University of Sfax, Sfax, Tunisia | [b] Laboratory of Computer and Automatic for System (LIAS), Poitiers National School of Engineering (ENSIP), University of Poitiers, Poitiers, France
Correspondence: [*] Corresponding author. M. Allouche, Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (Lab-STA), National School of Engineering of Sfax, University of Sfax, Postal Box 1173, 3038 Sfax, Tunisia. E-mail: [email protected].
Abstract: This paper presents a robust fuzzy control scheme for maximum power tracking of a photovoltaic (PV) pumping system dedicated to domestic use. This system is composed of a photovoltaic generator (PVG) supplying via a DC-DC boost converter, a DC motor coupled to a centrifugal pump. A knowledge dynamic model of the pumping system is firstly developed leading to a Takagi Sugeno (TS) representation by a simple convex polytopic transformation. This approach allows to reproduce the dynamic behavior of the system with accuracy over a wide operating range. Then, a robust T-S fuzzy MPPT controller is designed to track the reference speed and achieve an optimal operation of the photovoltaic pumping system. The proposed controller generates the optimal duty cycle to match the motor-pump impedance with the PV generator via a DC-DC converter, and thus, maximizes the quantity of water pumped daily. Finally, simulation results which take into account all changes in climatic conditions are presented for both transient and steady state operation.
Keywords: Fuzzy controller, H∞ performance, T-S fuzzy model, Maximum Power Point Tracking (MPPT), Linear Matrix Inequality (LMI)
DOI: 10.3233/JIFS-17400
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2521-2533, 2018
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]