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.
Bibliographical noteFunding 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.
© 2013 IEEE.
- Data-driven parameterization
- Hsuboptimal control
- fault estimation
- multiobjective optimization
ASJC Scopus subject areas
- Control and Systems Engineering
- Information Systems
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering