Model Discrimination of Switched Nonlinear Systems with Temporal Logic-Constrained Switching

Ruochen Niu, Syed M. Hassaan, Liren Yang, Zeyuan Jin, Sze Zheng Yong

Research output: Contribution to journalArticlepeer-review

Abstract

This paper considers the model discrimination problem for switched nonlinear systems, where the switching sequence is constrained by metric/signal temporal logic specifications. Specifically, we propose an optimization-based algorithm for analyzing the detectability of the models from noisy, finite data as well as a model discrimination algorithm for nonlinear parameter-varying systems to rule out models that are inconsistent with observations at run time, by checking the feasibility of corresponding mixed-integer linear programs. Moreover, we apply the algorithms to nonlinear systems subject to (m,k)-firm data losses and explicitly provide the integer constraints corresponding to the (m,k)-firm constraints for lossy/missing data. Finally, we demonstrate the effectiveness of our approaches using several illustrative examples on fault detection, swarm consensus and intent identification problems.

Original languageEnglish (US)
JournalIEEE Control Systems Letters
DOIs
StateAccepted/In press - 2021

Keywords

  • Analytical models
  • Computational modeling
  • Control systems
  • Data models
  • Encoding
  • Fault detection.
  • Model validation
  • Nonlinear systems
  • Switched systems
  • Switches

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

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