Improved model predictive control of discrete-time hybrid systems with mixed inputs

M. Gholami, K. Salahshoor, M. Tabatabaei-Pour, H. Shaker, T. Alizadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper suggests an improved method for predictive control of hybrid systems with mixed inputs. The algorithm takes into account the real nonlinear system as a model of a hybrid system, which is based on building a tree of evolution. Where the branch & bound (B&B) technique is applied for discrete controls in which an embedded nonlinear programming approach (Pattern search) is associated with each node of the tree in order to provide the continuous controls and explore the tree. Once the whole nodes of the tree are explored, the corresponding input is exploited to the system and the procedure is repeated. The performance of the resulting predictive control system is demonstrated on a motorboat simulation case study.

Original languageEnglish
Title of host publicationProceedings of the 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
Pages744-749
Number of pages6
DOIs
Publication statusPublished - Dec 1 2007
Event33rd Annual Conference of the IEEE Industrial Electronics Society, IECON - Taipei, Taiwan
Duration: Nov 5 2007Nov 8 2007

Publication series

NameIECON Proceedings (Industrial Electronics Conference)

Other

Other33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
CountryTaiwan
CityTaipei
Period11/5/0711/8/07

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Gholami, M., Salahshoor, K., Tabatabaei-Pour, M., Shaker, H., & Alizadeh, T. (2007). Improved model predictive control of discrete-time hybrid systems with mixed inputs. In Proceedings of the 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON (pp. 744-749). [4460321] (IECON Proceedings (Industrial Electronics Conference)). https://doi.org/10.1109/IECON.2007.4460321