Novel Looped Functionals in Designing Output Feedback Controllers for Aperiodic Sampled-Data Control Systems

This paper addresses the problem of stabilizing aperiodic sampled-data systems using output feedback control. First, a novel two-sided looped functional is constructed, providing a sufficient condition to ensure the asymptotic stability of the resulting closed-loop system. This condition is then adapted for control design. Using a cone complementary linearization algorithm with a stringent iteration criterion, a practical approach is developed to compute the control gain. Finally, three examples, including an inverted pendulum system and a one-area load-frequency control system, demonstrate the effectiveness and superiority of the proposed method over others in the literature.

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Publication Details

Journal
IEEE Transactions on Automation Science and Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/tase.2025.3573304
Citations
15
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
37.21

Funders

Controls
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article

Novel Looped Functionals in Designing Output Feedback Controllers for Aperiodic Sampled-Data Control Systems

Xian‐Ming Zhang, Hong‐Bing Zeng, Wei Wang, Jinming Liang
15 citations
IEEE Transactions on Automation Science and Engineering
Neural Networks and Applications
37.21
article

Novel Looped Functionals in Designing Output Feedback Controllers for Aperiodic Sampled-Data Control Systems

Xian‐Ming Zhang, Hong‐Bing Zeng, Wei Wang, Jinming Liang
article en
15 citations

Abstract

This paper addresses the problem of stabilizing aperiodic sampled-data systems using output feedback control. First, a novel two-sided looped functional is constructed, providing a sufficient condition to ensure the asymptotic stability of the resulting closed-loop system. This condition is then adapted for control design. Using a cone complementary linearization algorithm with a stringent iteration criterion, a practical approach is developed to compute the control gain. Finally, three examples, including an inverted pendulum system and a one-area load-frequency control system, demonstrate the effectiveness and superiority of the proposed method over others in the literature.

IEEE Transactions on Automation Science and EngineeringVol. 22
Hunan University of Technology (CN), Swinburne University of Technology (AU)
Natural Science Foundation of Hunan Province, Major Research Plan
Openalex Percentile: Top 0%
Neural Networks and Applications
37.21
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