30 Int. J. Computer Applications in Technology, Vol. 55, No. 1, 2017 Copyright © 2017 Inderscience Enterprises Ltd. Modelling and identification of an irrigation station using hybrid possibilistic c-means and fuzzy particle swarm optimisation Jaouher Chrouta*, Abderrahmen Zaafouri and Mohamed Jemli DGE, University of Tunis, 5 Av Taha Hussein, Tunis, Tunisia Email: chroutajawher@yahoo.fr Email: abderrahmen.zaafouri@isetr.rnu.tn Email: mohamedjemli2030@gmail.com *Corresponding author Abstract: Data-driven design of accurate and reliable Takagi–Sugeno (T-S) fuzzy systems has drawn the attention of several researchers in recent decades, according to an excellent ability for describing non-linear systems. In literature, several fuzzy clustering algorithms have been proposed to identify the parameters involved in the Takagi–Sugeno fuzzy model. Possibilistic C-Means (PCM) is one of the most used clustering methods because it is efficient, straightforward, easy to implement and exhibits robustness to noise. However, PCM is sensitive to initialisation and is easily trapped in local optima. Contrariwise, the PSO algorithm has strong global searching ability, and it doesn’t easily get into the local minimum to overcome the drawbacks of PCM algorithm. In this paper, a hybrid fuzzy clustering method based on PCM and fuzzy PSO (FPSO) is proposed which makes use of the merits of both algorithms. Experimental results applied to an irrigation station show that the hybrid algorithm (PCM-FPSO) is efficient and can reveal encouraging results. Keywords: irrigation station; fuzzy clustering; particle swarm optimisation; fuzzy particle swarm optimisation; Takagi–Sugeno fuzzy systems. Reference to this paper should be made as follows: Chrouta, J., Zaafouri, A. and Jemli, M. (2017) ‘Modelling and identification of an irrigation station using hybrid possibilistic c-means and fuzzy particle swarm optimisation’, Int. J. Computer Applications in Technology, Vol. 55, No. 1, pp.30–38. Biographical notes: Jaouher Chrouta received his BS and MS degree in Electrical Engineering in 2010 and 2012, respectively, from the High School of Sciences and Techniques of Tunis at University of Tunis, Tunisia. He is currently working towards the PhD degree at the same school. He is a member of a Research Unit on Control, Monitoring, and System of Safety (C3S). His research interests include identification and control of non-linear systems and in particular multiple model approach. Abderrahmen Zaafouri received a BSc in Electrical Engineering from the High Normal School of Technical Education of Tunis (ENSET) in 1993. In 1995, he obtained the Master’s degree in automatic control at the same university, and the PhD degree from the National Engineering School of Tunis in 2000; he joined the High School of Sciences and Techniques of Tunis (ESSTT) as an Assistant Professor. Now, he is a member of the Research Unit on Control, Monitoring and Safety of Systems (C3S) at ESSTT. His main research interests are approaches to robust control of uncertain systems. Mohamed Jemli received the BS and DEA degrees from the Ecole Superieure des Sciences et Techniques de Tunis (ESSTT), Tunisia, in 1985 and 1993, respectively, and the PhD degree from the Ecole Nationale dIngenieurs de Tunis (ENIT), in 2000, all in Electrical Engineering. From 1998 to 2001, he was an aggregate teacher at (ISET) de Rads. Since 2010, he was an Associate Professor at the High School of Sciences and Techniques of Tunis (ESSTT), Tunisia. His research is in the areas of electrical machines. This paper is a revised and expanded version of a paper entitled ‘Modeling and identification of an irrigation station using Possibilistic C means based on particle swarm optimization’ presented at the ‘2nd International Conference ACECS-2015’, Sousse, Tunisia, 22–24 March 2015.