Model predictive control for maintenance operations planning of railway infrastructures

October 20, 2015 in

Conference Paper

Ali Jamshidi

Zhou Zu, Alfredo Núñez, Ali Jamshidi, Simone Baldi, Zili Li, Rolf Dollevoet, Bart De Schutter


Year: October 2015
Location: Delft

Health condition monitoring and maintenance, Model Predictive Control (MPC), Railway engineering, Track maintenance

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This paper develops a new decision making method for optimal planning of railway maintenance operations using hybrid Model Predictive Control (MPC). A linear dynamic model is used to describe the evolution of the health condition of a segment of the railway track. The hybrid characteristics arise from the three possible control actions: performing no maintenance, performing corrective maintenance, or doing a replacement. A detailed procedure for transforming the linear system with switched input, and recasting the transformed problem into a standard mixed integer quadratic programming problem is presented. The merits of the proposed MPC approach for designing railway track maintenance plans are demonstrated using a case study with numerical simulations. The results highlight the potential of MPC to improve condition-based maintenance procedures for railway infrastructure.