A Model Predictive Control Framework for Improving Risk-Tolerance of Manufacturing Systems

Autor:	Anbarani, Mostafa Tavakkoli, Balta, Efe C., Meira-Góes, Rômulo, Kovalenko, Ilya
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	The need for control strategies that can address dynamic system uncertainty is becoming increasingly important. In this work, we propose a Model Predictive Control by quantifying the risk of failure in our system model. The proposed control scheme uses a Priced Timed Automata representation of the manufacturing system to promote the fail-safe operation of systems under uncertainties. The proposed method ensures that in case of unforeseen failure(s), the optimization-based control strategy can still achieve the manufacturing system objective. In addition, the proposed strategy establishes a trade-off between minimizing the cost and reducing failure risk to allow the manufacturing system to function effectively in the presence of uncertainties. An example from manufacturing systems is presented to show the application of the proposed control strategy. Comment: 7 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2302.08031 Zobrazit plný text záznamu View this record from Arxiv