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Volume 2017 (2017), Article ID 2017634, 11 pages
Research Article

Fuzzy Control Model and Simulation for Nonlinear Supply Chain System with Lead Times

1School of Logistics, Linyi University, Linyi 276005, China
2School of Economics and Management, Tongji University, Shanghai 200092, China
3Faculty of Business and Economics, The University of Melbourne, Melbourne, VIC 3010, Australia
4Library, Linyi University, Linyi 276005, China

Correspondence should be addressed to Songtao Zhang

Received 18 February 2017; Revised 4 June 2017; Accepted 13 August 2017; Published 14 September 2017

Academic Editor: Pietro De Lellis

Copyright © 2017 Songtao Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A new fuzzy robust control strategy for the nonlinear supply chain system in the presence of lead times is proposed. Based on Takagi-Sugeno fuzzy control system, the fuzzy control model of the nonlinear supply chain system with lead times is constructed. Additionally, we design a fuzzy robust control strategy taking the definition of maximal overlapped-rules group into consideration to restrain the impacts such as those caused by lead times, switching actions among submodels, and customers’ stochastic demands. This control strategy can not only guarantee that the nonlinear supply chain system is robustly asymptotically stable but also realize soft switching among subsystems of the nonlinear supply chain to make the less fluctuation of the system variables by introducing the membership function of fuzzy system. The comparisons between the proposed fuzzy robust control strategy and the robust control strategy are finally illustrated through numerical simulations on a two-stage nonlinear supply chain with lead times.