Model predictive control of dynamically substructured systems with application to a servohydraulically-actuated mechanical plant

G Li, DP Stoten, J-Y Tu

Research output: Contribution to journalArticle (Academic Journal)peer-review

24 Citations (Scopus)
298 Downloads (Pure)

Abstract

Dynamically substructured systems (DSS) are increasingly used by the dynamics testing community. DSS involves the physical testing of full size critical components in parallel with numerical testing of the remaining components. This has certain advantages over other testing methods. However, the synchronization of the signals at the interface between the physical and numerical substructures of DSS requires a high fidelity controller. In practice, the performance of the DSS testing can be significantly degraded by input saturation of the actuators. In this paper, we use model predictive control (MPC) to cope with the saturation problem in DSS. To facilitate the MPC and observer design for DSS, a modified DSS framework based on an existing one is proposed. As a case study, a quasi-motorcycle (QM) system is converted into the modified DSS framework and a traditional on-line MPC control strategy is implemented in real-time.
Translated title of the contributionModel predictive control of dynamically substructured systems with application to a servohydraulically-actuated mechanical plant
Original languageEnglish
Pages (from-to)253 - 264
Number of pages12
JournalIET Control Theory and Applications
Volume4
Issue number2
DOIs
Publication statusPublished - Feb 2010

Bibliographical note

Rose publication type: Journal article

Sponsorship: UK Engineering & Physical Sciences Research Council, grant number: EP/D0036917

Terms of use: This paper is a postprint of a paper submitted to and accepted for publication in IET Control Theory & Applications and is subject to Institution of Engineering and Technology Copyright.

Keywords

  • predictive control
  • substructured systems

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