Fault Estimation and Control for Unknown Discrete-Time Systems Based on Data-Driven Parameterization Approach

He Liu; Xiao Jian Li; Chao Deng; Choon Ki Ahn

doi:10.1109/TCYB.2021.3107425

Fault Estimation and Control for Unknown Discrete-Time Systems Based on Data-Driven Parameterization Approach

He Liu, Xiao Jian Li, Chao Deng, Choon Ki Ahn

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

This study investigates the problem of fault estimation and control for unknown discrete-time systems. Such a problem was first formulated as an H∞/H∞ multiobjective optimization problem. Then, a data-driven parameterization controller design method was proposed to optimize both fault estimation and robust control performances. In terms of the single-objection H∞ control problem, necessary and sufficient conditions for designing the H∞ suboptimal controller were presented, and the H∞ performance index optimized by the developed data-driven method was shown to be consistent with that of the model-based method. In addition, by introducing additional slack variables into the controller design conditions, the conservatism of solving the multiobjective optimization problem was reduced. Furthermore, contrary to the existing data-driven controller design methods, the initial stable controller was not required, and the controller gain was directly parameterized by the collected state and input data in this work. Finally, the effectiveness and advantages of the proposed method are shown in the simulation results.

Original language	English
Pages (from-to)	1629-1640
Number of pages	12
Journal	IEEE Transactions on Cybernetics
Volume	53
Issue number	3
DOIs	https://doi.org/10.1109/TCYB.2021.3107425
Publication status	Published - 2023 Mar 1

Bibliographical note

Funding Information:
This work was supported in part by the Funds of the National Natural Science Foundation of China under Grant 61873050; in part by the Fundamental Research Funds for the Central Universities under Grant N2004010; in part by the Research Fund of State Key Laboratory of Synthetical Automation for Process Industries under Grant 2018ZCX14; in part by the LiaoNing Revitalization Talents Program under Grant XLYC1907088; and in part by the National Research Foundation of Korea Grant funded by the Korea Government (Ministry of Science and ICT) under Grant NRF-2020R1A2C1005449.

Publisher Copyright:
© 2013 IEEE.

Keywords

Data-driven parameterization
Hsuboptimal control
fault estimation
multiobjective optimization

ASJC Scopus subject areas

Software
Control and Systems Engineering
Information Systems
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TCYB.2021.3107425

Cite this

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title = "Fault Estimation and Control for Unknown Discrete-Time Systems Based on Data-Driven Parameterization Approach",

abstract = "This study investigates the problem of fault estimation and control for unknown discrete-time systems. Such a problem was first formulated as an H∞/H∞ multiobjective optimization problem. Then, a data-driven parameterization controller design method was proposed to optimize both fault estimation and robust control performances. In terms of the single-objection H∞ control problem, necessary and sufficient conditions for designing the H∞ suboptimal controller were presented, and the H∞ performance index optimized by the developed data-driven method was shown to be consistent with that of the model-based method. In addition, by introducing additional slack variables into the controller design conditions, the conservatism of solving the multiobjective optimization problem was reduced. Furthermore, contrary to the existing data-driven controller design methods, the initial stable controller was not required, and the controller gain was directly parameterized by the collected state and input data in this work. Finally, the effectiveness and advantages of the proposed method are shown in the simulation results.",

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N2 - This study investigates the problem of fault estimation and control for unknown discrete-time systems. Such a problem was first formulated as an H∞/H∞ multiobjective optimization problem. Then, a data-driven parameterization controller design method was proposed to optimize both fault estimation and robust control performances. In terms of the single-objection H∞ control problem, necessary and sufficient conditions for designing the H∞ suboptimal controller were presented, and the H∞ performance index optimized by the developed data-driven method was shown to be consistent with that of the model-based method. In addition, by introducing additional slack variables into the controller design conditions, the conservatism of solving the multiobjective optimization problem was reduced. Furthermore, contrary to the existing data-driven controller design methods, the initial stable controller was not required, and the controller gain was directly parameterized by the collected state and input data in this work. Finally, the effectiveness and advantages of the proposed method are shown in the simulation results.

AB - This study investigates the problem of fault estimation and control for unknown discrete-time systems. Such a problem was first formulated as an H∞/H∞ multiobjective optimization problem. Then, a data-driven parameterization controller design method was proposed to optimize both fault estimation and robust control performances. In terms of the single-objection H∞ control problem, necessary and sufficient conditions for designing the H∞ suboptimal controller were presented, and the H∞ performance index optimized by the developed data-driven method was shown to be consistent with that of the model-based method. In addition, by introducing additional slack variables into the controller design conditions, the conservatism of solving the multiobjective optimization problem was reduced. Furthermore, contrary to the existing data-driven controller design methods, the initial stable controller was not required, and the controller gain was directly parameterized by the collected state and input data in this work. Finally, the effectiveness and advantages of the proposed method are shown in the simulation results.

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Fault Estimation and Control for Unknown Discrete-Time Systems Based on Data-Driven Parameterization Approach

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