Control and synchronization of chaotic supply chains using intelligent approaches

Kocamaz U. E., Taskin H., Uyaroglu Y., Goksu A.

COMPUTERS & INDUSTRIAL ENGINEERING, vol.102, pp.476-487, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 102
  • Publication Date: 2016
  • Doi Number: 10.1016/j.cie.2016.03.014
  • Journal Name: COMPUTERS & INDUSTRIAL ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.476-487
  • Keywords: Chaotic supply chain, Chaos control, Chaos synchronization, Artificial neural networks, Adaptive neuro-fuzzy inference system, SLIDING MODE CONTROL, NEURAL-NETWORK, DYNAMICAL-SYSTEMS, IMPULSIVE CONTROL, FEEDBACK-CONTROL, LINEAR FEEDBACK, FUZZY CONTROL, LIU SYSTEM, ROSSLER, DESIGN
  • Bursa Uludag University Affiliated: Yes

Abstract

This paper presents the control of chaotic supply chain with Artificial Neural Network (ANN) based controllers and the synchronization of two identical chaotic supply chains that have different initial conditions with Adaptive Neuro-Fuzzy Inference System (ANFIS) based controllers. A hybrid intelligent control model is designed in which the linear feedback and active control signals are also used for achieving the control and synchronization, respectively. ANN and ANFIS controllers are trained according to the model. Thereby, the advantages of classical and intelligent control methods are combined. Computer simulations show that the proposed approach is very effective for the control and synchronization of chaos in supply chain systems. (C) 2016 Elsevier Ltd. All rights reserved.