Xiaomo Wang | Searcharxiv

arXiv2026

Data-Driven Koopman Predictive Control for Frequency Regulation of Power Systems using Black-Box IBRs

Model uncertainty of inverter-based resources (IBRs) presents significant challenges for power system control and stability. This work studies secondary frequency regulation in inverter-based power systems using a Data-driven Koopman Predictive Control (DKPC) framework. The method employs Koopman theory to lift the nonlinear system dynamics into a higher-dimensional space where they can be approximated as linear. Based on Willems' fundamental lemma, a behavioral model is constructed directly from lifted input-output data. A receding-horizon predictive control formulation is then provided that operates entirely using observed data, without requiring a parametric model, while satisfying explicit constraints on the control input and system output. The proposed approach is particularly suited for IBRs with complex or uncertain dynamics. Numerical results demonstrate its effectiveness for frequency control as benchmarked against the Data-enabled Predictive Control (DeePC). The trade-off between tracking performance and control effort is illustrated through tuning of the weighting parameters.

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arXiv2024

SKYCASTLE: Taming LEO Mobility to Facilitate Seamless and Low-latency Satellite Internet Services

Emerging integrated space and terrestrial networks (ISTN) built upon low earth orbit (LEO) satellite constellations aim at providing planet-wide Internet services, not only for residential users, but also for mobile users (e.g., in airplane and cruise scenarios). Efficiently managing global mobility and keeping connections active for mobile users is critical for ISTN operators. However, our quantitative analysis identifies that existing mobility management (MM) schemes suffer from frequent connection interruptions and long latency in ISTN scenarios. The fundamental challenge stems from a unique characteristic of ISTNs: not only users are mobile, but also core network infrastructures (i.e., LEO satellites) are frequently changing their locations in the network. To facilitate seamless and low-latency satellite Internet services, this paper presents SKYCASTLE, a novel network-based global mobility management mechanism. SKYCASTLE incorporates two key techniques to address frequent connection interruptions in ISTNs. First, to reduce the interruption time, SKYCASTLE adopts distributed satellite anchors to track the location changes of mobile nodes, manage handovers and avoid routing convergence. Second, SKYCASTLE leverages an anchor manager to schedule MM functionalities at satellites to reduce deployment costs while guaranteeing low latency. Extensive evaluations combining real constellation information and mobile user trajectories show that: SKYCASTLE can improve up to 55.8% uninterrupted time and reduce 47.8% latency as compared to other existing MM solutions.

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