Data-Driven Human Modeling: Quantifying Personal Tendency Toward Laziness

Keita Hara, Masaki Inoue, Jose Maria Maestre

研究成果: Article査読

3 被引用数 (Scopus)

抄録

This letter addresses the modeling of a personal tendency by utilizing the data collected from a manned control system. In the control system, it is assumed that a control operator, namely a human controller, determines the control actions based on his/her tendency toward laziness. The tendency is described by a cost function that includes the L2 norm of the state and the L1 norm of the control action. Then, the operator behavior is modeled by the solution to the optimization problem formulated with the L2-state/L1-action cost function and the plant model. The tendency modeling is reduced to the problem of estimating the cost function. The estimation problem is further extended by taking into account the operator dynamics caused by the recognition and motion to derive an MPC-based formulation. Finally, the estimation method is demonstrated via an actual manned control experiment with a toy game.

本文言語English
論文番号9193972
ページ(範囲)1219-1224
ページ数6
ジャーナルIEEE Control Systems Letters
5
4
DOI
出版ステータスPublished - 2021 10月

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 制御と最適化

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