Systems & Control

Slava G. Turyshev

This paper provides a rigorous cost analysis for orbital data centers, highlighting the economic gap for general-purpose computing, which is relevant for space industry stakeholders evaluating data center investments.

An T. Le

This addresses the feasibility of energy extraction from black holes for theoretical physics and potential space applications, but it is incremental as it focuses on specific conditions and protocols.

Yixuan Zhu, Bo Zhang, Yinkang Gao et al.

This addresses a critical issue for real-time systems where precise latency bounds are essential, offering a novel solution that improves performance without significant trade-offs.

Zhenning Yang, Yuhan Chen, Patrick Tser Jern Kon et al.

For AI-for-science researchers and lab automation engineers, this work proposes a novel systems-level integration of AI agents with physical labs, though it remains a conceptual framework without empirical validation.

Jie Song, Yang Bai, Naoki Wakamiya

This addresses the challenge of autonomous cargo transport in multi-agent systems, offering a solution that is incremental by building on existing coordination methods like CVT and CBF.

Alan Veliz-Cuba, Zeyu Wang

This provides a modular approach for designing gene networks to achieve arbitrary phenotypes, addressing a specific problem in synthetic biology.

Mohammad Javad Khojasteh, Massimo Franceschetti, Gireeja Ranade

This work addresses the challenge of event-triggering control with zero-payload rate for systems like phone call networks, generalizing previous strategies and revealing fundamental limits in using timing information for stabilization.

Yuhan Chen, Tao Liu, Jie Huang

This solves a long-standing challenge in control theory for multi-agent systems, enabling applications like robotics and autonomous vehicles with unstable dynamics, though it is a foundational breakthrough rather than incremental.

Haoyu Wang, Alex Hanson

This system provides a faster and more robust solution for high-frequency magnetic characterization, benefiting designers of power magnetic components by improving the accuracy and speed of loss characterization.

Kim Hammar, Yuchao Li, Tansu Alpcan et al.

For network security practitioners, this method offers a scalable and theoretically grounded approach to adapt policies quickly to evolving threats and conditions.

Liang Chen

For financial economists and macro-finance researchers, the paper provides a sharper empirical target for testing constrained-intermediary models, though it does not definitively identify the mechanism.

Bo Wang, Miroslav Krstic

This work provides explicit constructive alternatives to CLF-CBF quadratic programming for scalar-input nonlinear systems, which is incremental as it builds on existing universal stabilizer formulas.

Yan Zhang, Indrakshi Dey, Nicola Marchetti

This work addresses performance enhancement for wireless networks, but it is incremental as it builds on existing RIS technology by adding movable antennas.

Yunxiang Ma, Yibo Wang, Zhongmei Li et al.

This work addresses control challenges in applications like power networks and chemical processes, offering a novel method for stochastic descriptor systems.

Peng Wang, Luis Badesa

For power system operators and regulators, this work highlights the vulnerability of SCC markets to strategic manipulation, emphasizing the need for careful market design to mitigate market power.

Donggeon David Oh, Duy P. Nguyen, Haimin Hu et al.

For safety-critical control of nonlinear systems with black-box dynamics and unknown uncertainty, this work provides a principled method to enforce safety on the maximal robust safe set.

Jason J. Choi, Donggun Lee, Boyang Li et al.

This work provides foundational insights for safe control policy design in systems with indefinite time horizons, though it is incremental in connecting existing concepts.

Ruixuan Zhao, Guitao Yang, James Fleming et al.

This work addresses a critical problem in cyber-physical systems and IoT for engineers and researchers, offering a more general solution compared to existing restrictive methods.

Linlin Li, Steven X. Ding, Jiahao Wang et al.

For control and fault detection researchers, it provides a theoretical foundation and practical method for data-driven fault detection in finite-sample settings.

Fangsheng Qian, Shuhan Chen, Wei Wei et al.

This work addresses a critical bottleneck in high-power acoustic wave devices for mobile handsets and emerging fields like quantum acoustics, enabling robust operation under high power loads.