Online Tradeoff Between Control Performance and Resource Occupation for Linear Systems Based on Hierarchical Self-Triggered Strategy

In this paper, a hierarchical self-triggered mechanism is designed to address real-time trade-offs between control performance and resource utilization in linear systems, accompanied by detailed control and triggering strategies. Specifically, a hierarchical strategy is employed in this approach. The upper layer dynamically assigns trigger cost and control cost weights according to the realtime system state, while the lower layer calculates the optimal inter-execution interval value and control input based on the given weights at the current time. To simultaneously account for control costs and triggering consumption within the self-triggered mechanism, an integrated objective function is introduced. This function is based on the weighted fusion of trigger utilization and control performance, initially utilized in the upper layer to compute the weight values for trigger and control using the influence function. Subsequently, in the lower layer, by minimizing the objective function with the updated weight coefficients, the upcoming triggering time can be forecasted, and the control input within the triggering interval can be determined. By integrating upper-level decision-making with lower-level execution, this innovative self-triggered control mechanism effectively maintains a balance between control performance and triggering cost across various scenarios, expanding its applicability. Finally, a numerical simulation example shows the effectiveness of the method.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-08-25
DOI
https://doi.org/10.1109/tac.2025.3602091
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Online Tradeoff Between Control Performance and Resource Occupation for Linear Systems Based on Hierarchical Self-Triggered Strategy

Xiaoli Luan, Haiying Wan, Chenyang Wang, Fei Liu
IEEE Transactions on Automatic Control
Neural Networks and Applications
article

Online Tradeoff Between Control Performance and Resource Occupation for Linear Systems Based on Hierarchical Self-Triggered Strategy

Xiaoli Luan, Haiying Wan, Chenyang Wang, Fei Liu
article en

Abstract

In this paper, a hierarchical self-triggered mechanism is designed to address real-time trade-offs between control performance and resource utilization in linear systems, accompanied by detailed control and triggering strategies. Specifically, a hierarchical strategy is employed in this approach. The upper layer dynamically assigns trigger cost and control cost weights according to the realtime system state, while the lower layer calculates the optimal inter-execution interval value and control input based on the given weights at the current time. To simultaneously account for control costs and triggering consumption within the self-triggered mechanism, an integrated objective function is introduced. This function is based on the weighted fusion of trigger utilization and control performance, initially utilized in the upper layer to compute the weight values for trigger and control using the influence function. Subsequently, in the lower layer, by minimizing the objective function with the updated weight coefficients, the upcoming triggering time can be forecasted, and the control input within the triggering interval can be determined. By integrating upper-level decision-making with lower-level execution, this innovative self-triggered control mechanism effectively maintains a balance between control performance and triggering cost across various scenarios, expanding its applicability. Finally, a numerical simulation example shows the effectiveness of the method.

IEEE Transactions on Automatic ControlVol. 71(1)
Jiangnan University (CN)
Decent work and economic growth
Openalex Percentile: Top 88%
Neural Networks and Applications
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