A Takagi-Sugeno Fuzzy Model for Greenhouse Climate
Received: 14 June 2021 | Revised: 30 June 2021 | Accepted: 3 July 2021 | Online: 21 August 2021
Corresponding author: I. Haj Hamad
Abstract
This paper investigates the identification and modeling of a greenhouse's climate using real climate data from a greenhouse installed in the LAPER laboratory in Tunisia. The objective of this paper is to propose a solution to the problem of nonlinear time-variant inputs and outputs of greenhouse internal climate. Combining fuzzy logic technique with Least Mean Squares (LMS), a robust greenhouse climate model for internal temperature prediction is proposed. The simulation results demonstrate the effectiveness of the identification approach and the power of the implemented Takagi-Sugeno Fuzzy model-based algorithm.
Keywords:
TS fuzzy modeling, climate greenhouse, fuzzy clustering, identificationDownloads
References
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