TY - JOUR
T1 - Data-Driven Human Modeling
T2 - Quantifying Personal Tendency Toward Laziness
AU - Hara, Keita
AU - Inoue, Masaki
AU - Maestre, Jose Maria
N1 - Funding Information:
Manuscript received June 23, 2020; revised August 11, 2020; accepted August 28, 2020. Date of publication September 10, 2020; date of current version September 25, 2020. This work was supported in part by the Grant-in-Aid for Scientific Research (B), through JSPS under Grant 20H02173, and in part by the Project C3PO, through Spanish Ministry of Economy under Grant DPI2017-86918-R. Recommended by Senior Editor L. Menini. (Corresponding author: Masaki Inoue.) Keita Hara and Masaki Inoue are with the Department of Applied Physics and Physico-Informatics, Keio University, Kanagawa 211-0053, Japan (e-mail: reds@keio.jp; minoue@appi.keio.ac.jp).
Publisher Copyright:
© 2017 IEEE.
PY - 2021/10
Y1 - 2021/10
N2 - 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.
AB - 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.
KW - Human tendency modeling
KW - L2/L1 optimal control
KW - model predictive control
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U2 - 10.1109/LCSYS.2020.3023337
DO - 10.1109/LCSYS.2020.3023337
M3 - Article
AN - SCOPUS:85093980143
SN - 2475-1456
VL - 5
SP - 1219
EP - 1224
JO - IEEE Control Systems Letters
JF - IEEE Control Systems Letters
IS - 4
M1 - 9193972
ER -