Abstract

As a complex and nonlinear systems characterized by inherent delays, supply chains call for more robust and efficient strategies for their dynamic management. Given the inherent modeling challenges that often fail to capture their dynamic behavior, this paper examines the application of model-free control, as introduced by Fliess and Join, to address supply chain management (SCM) issues. The proposed control framework integrates the principles of model-free control, further enriched by recent advancements in time series analysis for delay compensation and customer demand forecasting. The primary objective, in addition to ensuring effective supply chain control, is to mitigate the intriguing bullwhip effect, where the system model is assumed unknown, and the delay is constant yet unknown. To substantiate this approach’s effectiveness, we present several convincing computer simulations using real-world examples and compare the results with the internal model control strategy.

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