This paper proposes a new modeling and control methodology for allocating materials in a dry bulk terminal with a finite storage capacity. The dynamical process of material storage allocation in the terminal is modeled using a hybrid system perspective that combines both discrete-event and continuous-time dynamics. The stockyard space is partitioned into a number of slots for exchanging incoming and outgoing material flows in the terminal, leading to a so-called mixed logical dynamical (MLD) model with the maximal storage capacity. Based on the MLD model, a model predictive controller is then proposed for maximizing the economic profit in a rolling horizon manner. A number of Monte Carlo simulations have been performed involving a real case study for analyzing the effects of different slot volumes on the economic performance and the computational performance of the controller. Simulations also demonstrate the potential of the proposed methodology.

Original languageEnglish
Pages (from-to)1326-1336
JournalIEEE Transactions on Automation Science and Engineering
Volume15
Issue number3
DOIs
Publication statusPublished - 2018

    Research areas

  • Computational modeling, Dry bulk terminals, Economics, hybrid systems, Marine vehicles, material allocation, Material storage, Mathematical model, model predictive control., Predictive models, Resource management

ID: 43643544