“Weak” Control for Human-in-the-loop Systems

Masaki Inoue, Vijay Gupta

Research output: Contribution to journalArticle

Abstract

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
JournalIEEE Control Systems Letters
DOIs
Publication statusAccepted/In press - 2019 Jan 1

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Controller
Controllers
Costs
Feedback Loop
Learning algorithms
Learning Algorithm
Choose
Update
Control System
Numerical Experiment
Human
Feedback
Minimise
Control systems
Output
Experiments
Framework

Keywords

  • Control systems
  • Decision making
  • Erbium
  • Feedback loop
  • Human-in-the-loop system
  • internal model control
  • optimization
  • Robust control
  • robust control.
  • stability
  • Stability analysis
  • Uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

Cite this

“Weak” Control for Human-in-the-loop Systems. / Inoue, Masaki; Gupta, Vijay.

In: IEEE Control Systems Letters, 01.01.2019.

Research output: Contribution to journalArticle

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