'Weak' control for human-in-the-loop systems

Masaki Inoue, Vijay Gupta

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


We propose a control framework for human-in-the-loop systems, in which many human decision makers are involved in the feedback loop composed of a plant and a controller. The novelty of the framework is that the decision makers are weakly controlled; in other words, they receive a set of admissible control actions from the controller and choose one of them in accordance with their private preferences. For example, the decision makers can decide their actions to minimize their own costs or by simply relying on their experience and intuition. A class of controllers which output set-valued signals is designed such that the overall control system is stable independently of the decisions made by the humans. Finally, a learning algorithm is applied to the controller that updates the controller parameters to reduce the achievable minimal costs for the decision makers. Effective use of the algorithm is demonstrated in a numerical experiment.

Original languageEnglish
Article number8606069
Pages (from-to)440-445
Number of pages6
JournalIEEE Control Systems Letters
Issue number2
Publication statusPublished - 2019 Apr


  • Human-in-the-loop system
  • internal model control
  • optimization
  • robust control
  • stability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization


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