DYNAMICAL INVESTIGATION AND DISTRIBUTED CONSENSUS TRACKING CONTROL OF A VARIABLE-ORDER FRACTIONAL SUPPLY CHAIN NETWORK USING A MULTI-AGENT NEURAL NETWORK-BASED CONTROL METHOD

Tian-Chuan Sun, Amin Yousefpour, Yeliz Karaca, Madini O. Alassafi, Adil M. Ahmad and Yong-Min Li
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Tian-Chuan Sun: Public Teaching and Research Department, Huzhou College, Huzhou 313000, P. R. China
Amin Yousefpour: ��Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA 92697, USA
Yeliz Karaca: ��University of Massachusetts Medical School, Worcester, MA 01655, USA
Madini O. Alassafi: �Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
Adil M. Ahmad: �Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
Yong-Min Li: �Department of Mathematics, Huzhou University, Huzhou 313000, P. R. China∥Institute for Advanced Study Honoring Chen Jian Gong, Hangzhou Normal University, Hangzhou 311121, P. R. China

FRACTALS (fractals), 2022, vol. 30, issue 05, 1-13

Abstract: In today’s sophisticated global marketplace, supply chains are complex nonlinear systems in the presence of different types of uncertainties, including supply-demand and delivery uncertainties. Though up to now, some features of these systems are studied, there are still many aspects of these systems which need more attention. This necessitates more research studies on these systems. Hence, in this study, we propose a variable-order fractional supply chain network. The dynamic of the system is investigated using the Lyapunov exponent and bifurcation diagram. It is demonstrated that a minor change in the system’s fractional-derivative may dramatically affect its behavior. Then, distributed consensus tracking of the multi-agent network is studied. To this end, a control technique based on the sliding concept and Chebyshev neural network estimator is offered. The system’s stability is demonstrated using the Lyapunov stability theorem and Barbalat’s lemma. Finally, through numerical results, the proposed controller’s excellent performance for distributed consensus tracking of multi-agent supply chain network is demonstrated.

Keywords: Supply Chain; Finance; Economy; Fractional Calculus; Robust Fuzzy Adaptive Technique; Adaptation Mechanism (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218348X22401685

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