Real-Time Dynamic-Mode Scheduling Using Single-Integration Hybrid Optimization

Anastasia Mavrommati, Jarvis Schultz, Todd D. Murphey

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


This paper introduces and implements a method for real-time mode scheduling in linear time-varying switched systems subject to a quadratic cost functional. The execution time of switched system algorithms is often prohibitive for real-time applications and typically may only be reduced at the expense of approximation accuracy. We address this tradeoff by taking advantage of system linearity to formulate a projection-based approach, such that no simulation is required during open-loop optimization. A numerical example shows how the proposed open-loop algorithm outperforms the methods employing common numerical integration techniques. In addition, we follow a receding-horizon scheme to schedule the modes of a customized experimental setup in real time, using the robot operating system. In particular, we demonstrate - both in Monte Carlo simulation and in experiment - that optimal mode scheduling efficiently regulates a cart and suspended mass system and rejects disturbances online.

Original languageEnglish (US)
Article number7486041
Pages (from-to)1385-1398
Number of pages14
JournalIEEE Transactions on Automation Science and Engineering
Issue number3
StatePublished - Jul 2016


  • Optimal control
  • real-time experimental validation
  • receding-horizon control
  • switching controllers

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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