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| Coprime factors based robust control-oriented identification of errors-in-variables systems in output feedbacks |
| Li-HuiGeng1,Guo-FengJi1,Yong-LiZhang1 |
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| (Tianjin Key Laboratory of Information Sensing and Intelligent Control, School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China) |
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| 摘要: |
| This paper proposes a robust control-oriented identification method for errors-in-variables (EIV) systems in output feedbacks using frequency-response (FR) experimental data. An important relation between such a closed-loop EIV system and its coprime factor (CF) uncertainty description is first derived, based on which the FR measurements suitable for plant CF identification are able to be generated. Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors (RCFs) of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data. Subsequently, a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system. A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds. Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis. Finally, a numerical simulation is given to show the efficacy of the proposed identification method. |
| 关键词: Robust control-oriented identification · Errors-in-variables system · Output feedback · Right coprime factors · Frequency response |
| DOI：https://doi.org/10.1007/s11768-025-00272-8 |
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| 基金项目: |
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| Coprime factors based robust control-oriented identification of errors-in-variables systems in output feedbacks |
| Li-Hui Geng1,Guo-Feng Ji1,Yong-Li Zhang1 |
| (Tianjin Key Laboratory of Information Sensing and Intelligent Control, School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China) |
| Abstract: |
| This paper proposes a robust control-oriented identification method for errors-in-variables (EIV) systems in output feedbacks using frequency-response (FR) experimental data. An important relation between such a closed-loop EIV system and its coprime factor (CF) uncertainty description is first derived, based on which the FR measurements suitable for plant CF identification are able to be generated. Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors (RCFs) of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data. Subsequently, a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system. A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds. Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis. Finally, a numerical simulation is given to show the efficacy of the proposed identification method. |
| Key words: Robust control-oriented identification · Errors-in-variables system · Output feedback · Right coprime factors · Frequency response |
