pwc-archive/papers-with-abstracts huggingface dataset:
Fundamental Techniques for Optimal Control of Reconfigurable Battery Systems: System Modeling and Feasible Search Space Construction
Authors: Changyou Geng, Dezhi Ren, Enkai Mao, Changfu Zou, Mario Vašak, Xinyi Zheng, Weiji Han
Date: 2025-01-06 00:00:00

Reconfigurable battery systems (RBSs) are emerging as a promising solution to improving fault tolerance, charge and thermal balance, energy delivery, etc. To optimize these performance metrics of RBSs, high-dimensional nonlinear integer programming problems need to be formulated and solved. To accomplish this, it is necessary to address several critical challenges stemming from nonlinear battery characteristics, discrete switch states, dynamic system configurations, as well as the curse of dimensionality inherent in large-scale RBSs. Thus, we propose a unified modeling framework to accommodate various possible configurations of an RBS and even to cover different RBS designs and their hybrid combinations, enabling the problem formulation for the RBS optimal control and facilitating the RBS topology design.Further, to solve the formulated RBS optimal control problems, the search space is narrowed to encompass only the feasible solutions, thereby ensuring safe battery connections while substantially curtailing search efforts. These proposed techniques, focusing on unifying the system modeling and narrowing the search space, lay a solid foundation for effectively formulating and efficiently solving RBS optimal control problems. The accuracy and effectiveness of the proposed techniques are demonstrated by both simulation and experimental tests.
AC-aware Optimization Framework for Under-Frequency Load Shedding
Authors: Mazen Elsaadany, Muhammad Hamza Ali, Amritanshu Pandey, Mads R. Almassalkhi
Date: 2025-01-06 00:00:00

Under-frequency load shedding (UFLS) prevents system collapse during large disturbances. Increased penetration of distributed energy resources (DERs) and reduced system inertia makes it challenging to design a static UFLS scheme, which relies on preset frequency thresholds and load shed fractions to meet design criteria across all possible operating conditions. Due to non-linearity and traceability issues, previous adaptive UFLS schemes use simplified tractable frequency models that overlook AC network effects such as voltage-dependent load/generation. This paper leverages model order reduction techniques to obtain a higher fidelity low-order model of system frequency dynamics that captures AC network effects while incorporating turbine governor action and their associated limits. The model is then used in a new AC-aware predictive optimization framework to adapt UFLS setpoints periodically based on current operating conditions while minimizing load shed. Validated on a 1,648-bus system with PSS/E simulations, the proposed method meets design criteria under various operating conditions and disturbance scenarios. Furthermore, the framework outperforms conventional static UFLS schemes and adaptive UFLS schemes based on simplified dynamic models.
Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions
Authors: Jianhua Pei, Ping Wang, Jingyu Wang, Dongyuan Shi
Date: 2025-01-06 00:00:00
Tasks: State Estimation

Fast and robust dynamic state estimation (DSE) is essential for accurately capturing the internal dynamic processes of power systems, and it serves as the foundation for reliably implementing real-time dynamic modeling, monitoring, and control applications. Nonetheless, on one hand, traditional DSE methods based on Kalman filtering or particle filtering have high accuracy requirements for system parameters, control inputs, phasor measurement unit (PMU) data, and centralized DSE communication. Consequently, these methods often face accuracy bottlenecks when dealing with structural or system process errors, unknown control vectors, PMU anomalies, and communication contingencies. On the other hand, deep learning-aided DSE, while parameter-free, often suffers from generalization issues under unforeseen operating conditions. To address these challenges, this paper proposes an effective approach that leverages deep generative models from AI-generated content (AIGC) to assist DSE. The proposed approach employs an encoder-decoder architecture to estimate unknown control input variables, a robust encoder to mitigate the impact of bad PMU data, and latent diffusion model to address communication issues in centralized DSE. Additionally, a lightweight adaptor is designed to quickly adjust the latent vector distribution. Extensive experimental results on the IEEE 39-bus system and the NPCC 140-bus system demonstrate the effectiveness and superiority of the proposed method in addressing DSE modeling imperfection, measurement uncertainties, communication contingencies, and unknown distribution challenges, while also proving its ability to reduce data storage and communication resource requirements.
Learning Control for LQR with Unknown Packet Loss Rate Using Finite Channel Samples
Authors: Zhenning Zhang, Liang Xu, Yilin Mo, Xiaofan Wang
Date: 2025-01-06 00:00:00

This paper studies the linear quadratic regulator (LQR) problem over an unknown Bernoulli packet loss channel. The unknown loss rate is estimated using finite channel samples and a certainty-equivalence (CE) optimal controller is then designed by treating the estimate as the true rate. The stabilizing capability and sub-optimality of the CE controller critically depend on the estimation error of loss rate. For discrete-time linear systems, we provide a stability threshold for the estimation error to ensure closed-loop stability, and analytically quantify the sub-optimality in terms of the estimation error and the difference in modified Riccati equations. Next, we derive the upper bound on sample complexity for the CE controller to be stabilizing. Tailored results with less conservatism are delivered for scalar systems and n-dimensional systems with invertible input matrix. Moreover, we establish a sufficient condition, independent of the unknown loss rate, to verify whether the CE controller is stabilizing in a probabilistic sense. Finally, numerical examples are used to validate our results.
A Volumetric Approach to Privacy of Dynamical Systems
Authors: Chuanghong Weng, Ehsan Nekouei
Date: 2025-01-06 00:00:00
Tasks: Inference Attack

Information-theoretic metrics, such as mutual information, have been widely used to evaluate privacy leakage in dynamic systems. However, these approaches are typically limited to stochastic systems and face computational challenges. In this paper, we introduce a novel volumetric framework for analyzing privacy in systems affected by unknown but bounded noise. Our model considers a dynamic system comprising public and private states, where an observation set of the public state is released. An adversary utilizes the observed public state to infer an uncertainty set of the private state, referred to as the inference attack. We define the evolution dynamics of these inference attacks and quantify the privacy level of the private state using the volume of its uncertainty sets. We then develop an approximate computation method leveraging interval analysis to compute the private state set. We investigate the properties of the proposed volumetric privacy measure and demonstrate that it is bounded by the information gain derived from the observation set. Furthermore, we propose an optimization approach to designing privacy filter using randomization and linear programming based on the proposed privacy measure. The effectiveness of the optimal privacy filter design is evaluated through a production-inventory case study, illustrating its robustness against inference attacks and its superiority compared to a truncated Gaussian mechanism.
Ray-Tracing Channel Modeling for LEO Satellite-to-Ground Communication Systems
Authors: Jiahao Ning, Jinhao Deng, YuanFang Li, Chi Zhao, Jiashu Liu, Songjiang Yang, Yinghua Wang, Jie Huang, Cheng-Xiang Wang
Date: 2025-01-06 00:00:00

Based on the vision of global coverage for sixth-generation (6G) wireless communication systems, the low earth orbit (LEO) satellite-to-ground channel model for urban scenarios has emerged as highly important for the system design. In this paper, we propose an LEO satellite-to-ground channel model through shooting and bouncing rays (SBR) algorithm to analyze the channel characteristics. The orbit of LEO is modeled by the simplified general perturbations 4 (SGP4), and an accurate celestial model is applied to calculate the Doppler shift of multipath in a transmission time window of LEO satellite-to-ground communications. Channel characteristics of LEO satellite-to-ground communications such as the root-mean-square (RMS) delay spread, the Doppler shift, and the received power at different times are obtained. The simulation results show that the received power is only significantly noticeable in the transmission time window when the satellite is close to the receiver. Proposed model validates the effectiveness of ray-tracing in actual LEO satellite-to-ground communication scenarios and extends the calculation of the Doppler shift.
Gaming on Coincident Peak Shaving: Equilibrium and Strategic Behavior
Authors: Liudong Chen, Jay Sethuraman, Bolun Xu
Date: 2025-01-06 00:00:00

Power system operators and electric utility companies often impose a coincident peak demand charge on customers when the aggregate system demand reaches its maximum. This charge incentivizes customers to strategically shift their peak usage away from the system's collective peak, which helps reduce stress on electricity infrastructure. In this paper, we develop a game-theoretic model to analyze how such strategic behavior affects overall system efficiency. We show that depending on the extent of customers' demand-shifting capabilities, the resulting coincident peak shaving game can exhibit concavity, quasi-concavity with discontinuities, or non-concavity with discontinuities. In a two-agent, two-period setting, we derive closed-form Nash equilibrium solutions for each scenario and generalize our findings to multi-agent contexts. We prove the stability of the equilibrium points and propose an algorithm for computing equilibrium outcomes under all game configurations. Our results indicate that the peak-shaving outcome at the equilibrium of the game model is comparable to the optimal outcome of the natural centralized model. However, there is a significant loss in efficiency. Under quasi-concave and non-concave conditions, this inefficiency grows with increased customer flexibility and larger disparities in marginal shifting costs; we also examine how the number of agents influences system performance. Finally, numerical simulations with real-world applications validate our theoretical insights.
Multi-Transmission Node DER Aggregation: Chance-Constrained Unit Commitment with Bounded Hetero-Dimensional Mixture Model for Uncertain Distribution Factors
Authors: Weilun Wang, Zhentong Shao, Yikui Liu, Brent Eldridge, Abhishek Somani, Jesse T. Holzer, Lei Wu
Date: 2025-01-06 00:00:00

To facilitate the integration of distributed energy resources (DERs) into the wholesale market while maintaining the tractability of associated market operation tools such as unit commitment (UC), existing DER aggregation (DERA) studies usually consider that each DERA is presented on a single node of the transmission network. Nevertheless, the increasing scale and geographical distribution of DERs spur the emergence of DERAs covering multiple transmission nodes, posing new challenges in modeling such multi-transmission-node DERAs (M-DERAs). Indeed, assessing the aggregated impact of an M-DERA on power flows is a non-trivial task, because the sensitivities of each transmission line to DERs at different transmission nodes are not identical. Inspired by the distribution factor (DF) based shift factor (SF) aggregation strategy in industry practice, this paper proposes a novel DF-based chance-constrained UC (CCUC) model to determine system optimal operation plans with M-DERAs. DFs, treated as uncertain parameters to describe possible responses of DERs against aggregated dispatch instructions from regional transmission organizations, are modeled via a bounded hetero-dimensional mixture model (BHMM) by leveraging historical DF records distributed on multiple hyperplanes in a bounded space. With this, power flow limits are modeled as chance constraints in CCUC, which is reformulated into a scenarios-based stochastic form and solved by Benders decomposition. The proposed method is tested on an IEEE 24-bus system to illustrate its effectiveness in managing M-DERA integration while ensuring operational economics and mitigating the overloading of transmission lines.
A Novel First-Principles Model of Injection-Locked Oscillator Phase Noise
Authors: Torsten Djurhuus, Viktor Krozer
Date: 2025-01-05 00:00:00

The paper documents the development of a novel time-domain model of injection-locked oscillator phase-noise response. The methodology follows a first-principle approach and applies to all circuit topologies, coupling configurations, parameter dependencies etc. The corresponding numerical algorithm is readily integrated into all major commercial simulation software suites. The model advances current state-of-the-art pertaining to analytical modelling of this class of circuits. Using this novel analytical framework, several important new insights are revealed which, in-turn, translate into useful design rules for synthesis of injection-locked oscillator circuits with optimal noise performance.
Low RCS High-Gain Broadband Substrate Integrated Waveguide Antenna Based on Elliptical Polarization Conversion Metasurface
Authors: Cuiqin Zhao, Dongya Shen, Yanming Duan, Yuting Wang, Huihui Xiao, Longxiang Luo
Date: 2025-01-05 00:00:00

Designed an elliptical polarization conversion metasurface (PCM) for Ka-band applications, alongside a high-gain substrate integrated waveguide (SIW) antenna. The PCM elements are integrated into the antenna design in a chessboard array configuration, with the goal of achieving effective reduction in the antenna's radar cross section (RCS). Both the PCM elements and antenna structure exhibit a simple design. The top layer of the metasurface (MS) elements employs an elliptical pattern symmetric along the diagonal, enabling efficient conversion of linearly polarized waves. The antenna component, on the other hand, consists of a broadband dipole antenna fed by SIW slot coupling. Verified through simulations, the polarization conversion bandwidth of this PCM unit reaches 80.38% where polarization conversion ratio (PCR) exceeds 90% (25.3-59.3GHz), demonstrating exceptional conversion performance. When the dipole antenna is combined with the PCM, its -10dB impedance bandwidth reaches to 15.09% (33.7-39.2GHz), with a maximum realized gain of 9.1dBi. Notably, the antenna loaded with the chessboard PCM structure effectively disperses the energy of scattered echoes around, significantly reducing the concentration of scattered energy in the direction of the incident wave, thereby achieving an effective reduction in RCS.
EOG Communication Interface for Quadriplegics: Prototype & Signal Processing
Authors: Aniket Raj, Amit Kumar
Date: 2025-01-05 00:00:00

Electrooculography (EOG) is an electrophysiological signal that determines the human eye orientation and is therefore widely used in Human Tracking Interfaces (HCI). The purpose of this project is to develop a communication method for quadriplegic patients using EOG signals aimed at text and voice generation. The system consists of 3D eye movement tracking embedded using a custom-built prototype to measure the eyeball's left-right and up-down movements. The ESP32 board, which has a set of parameters to convert the data into content displayed on LCDs and MP3 players, is used to capture and process the signal. helps people by facilitating more natural and efficient symptom expression. The blink system will be able to incorporate face masks and more eye tests as it continues to develop. Even if it might work, more research and clinical trials are needed to evaluate the system's usefulness and ensure that it performs as planned in real-world scenarios. With this project, assistive technology will make significant progress and improve the lives of many who suffer from severe motor impairments.
On Symmetries in Analytic Input-Output Systems
Authors: W. Steven Gray, Erik I. Verriest
Date: 2025-01-04 00:00:00
Tasks: State Space Models

There are many notions of symmetry for state space models. They play a role in understanding when systems are time reversible, provide a system theoretic interpretation of thermodynamics, and have applications in certain stabilization and optimal control problems. The earliest form of symmetry for analytic input-output systems is due to Fliess who introduced systems described by an exchangeable generating series. In this case, one is able to write the output as a memoryless analytic function of the integral of each input. The first goal of this paper is to describe two new types of symmetry for such Chen--Fliess input-output systems, namely, coefficient reversible symmetry and palindromic symmetry. Each concept is then related to the notion of an exchangeable series. The second goal of the paper is to provide an in-depth analysis of Chen--Fliess input-output systems whose generating series are linear time-varying, palindromic, and have generating series coefficients growing at a maximal rate while ensuring some type of convergence. It is shown that such series have an infinite Hankel rank and Lie rank, have a certain infinite dimensional state space realization, and a description of their relative degree and zero dynamics is given.
Stochastic Generalized Dynamic Games with Coupled Chance Constraints
Authors: Seyed Shahram Yadollahi, Hamed Kebriaei, Sadegh Soudjani
Date: 2025-01-04 00:00:00

Designing multi-agent systems with safety constraints and uncertain dynamics is a challenging problem. This paper studies a stochastic dynamic non-cooperative game with coupling safety chance constraints. The uncertainty is assumed to satisfy a concentration of measure property. Firstly, due to the non-convexity of chance constraints, a convex under-approximation of chance constraints is given using constraints on the expectation. Then, the conditions for the existence of the stochastic generalized Nash equilibrium (SGNE) of the under-approximated game are investigated, and the relation between the $\varepsilon-$SGNE of the original game and the under-approximated one is derived. A sampling-based algorithm is proposed for the SGNE seeking of the under-approximated game that does not require knowing the distribution of the uncertainty nor the analytical computation of expectations. Finally, under some assumptions on the game's pseudo-gradient mapping, the almost sure convergence of the algorithm to SGNE is proven. A numerical study is carried out on demand-side management in microgrids with shared battery to demonstrate the applicability of the proposed scheme.
SMTL: A Stratified Logic for Expressive Multi-Level Temporal Specifications
Authors: Ali Baheri, Peng Wei
Date: 2025-01-03 00:00:00

We present Stratified Metric Temporal Logic (SMTL), a novel formalism for specifying and verifying properties of complex cyber-physical systems that exhibit behaviors across multiple temporal and abstraction scales. SMTL extends existing temporal logics by incorporating a stratification operator, enabling the association of temporal properties with specific abstraction levels. This allows for the natural expression of multi-scale requirements while maintaining formal reasoning about inter-level relationships. We formalize the syntax and semantics of SMTL, proving that it strictly subsumes metric temporal logic (MTL) and offers enhanced expressiveness by capturing properties unattainable in existing logics. Numerical simulations comparing agents operating under MTL and SMTL specifications show that SMTL enhances agent coordination and safety, reducing collision rates without substantial computational overhead or compromising path efficiency. These findings underscore SMTL's potential as a valuable tool for designing and verifying complex multi-agent systems operating across diverse temporal and abstraction scales.
Distributed Framework Construction for Affine Formation Control
Authors: Huiming Li, Hao Chen, Xiangke Wang, Zhongkui Li, Lincheng Shen
Date: 2025-01-03 00:00:00

In affine formation control problems, the construction of the framework with universal rigidity and affine localizability is a critical prerequisite, but it has not yet been well addressed, especially when additional agents join the formation or link/agent failures emerge. Motivated by this observation, we investigate the problem of constructing affine frameworks in three scenarios, including vertex addition, edge deletion and vertex deletion. Our approach starts from the original affine formation and uses geometric methods to locally adjust the structure of the weighted graph to describe the topology, so that the modified framework maintains the universal rigidity and affine localizability. Notably, the developed strategies only utilize local measurements and exhibit distributed characteristics, laying the foundation for applications in multi-agent systems. To demonstrate the compatibility with affine formation control proposals, we present a case study on affine formation tracking in a multi-UAV formation, demonstrating the effectiveness of our algorithms in constructing eligible frameworks in aforementioned scenarios. Moreover, a comparative simulation is also conducted to highlight the low time complexity of our distributed algorithm relative to the centralized optimization-based method.
Smooth Rate Limiter Model for Power System Stability Analysis and Control
Authors: Zaint A. Alexakis, Panos C. Papageorgiou, Antonio T. Alexandridis, Federico Milano, Georgios Tzounas
Date: 2025-01-03 00:00:00

The letter proposes a smooth Rate Limiter (RL) model for power system stability analysis and control. The proposed model enables the effects of derivative bounds to be incorporated into system eigenvalue analysis, while replicating the behavior of conventional non-smooth RLs with high fidelity. In addition, it can be duly modified to enhance the system's dynamic control performance. The behavior of the proposed model is demonstrated through illustrative examples as well as through a simulation of the New York/New England 16-machine 68-bus system.
Sensor Placement on a Cantilever Beam Using Observability Gramians
Authors: Natalie L. Brace, Nicholas B. Andrews, Jeremy Upsal, Kristi A. Morgansen
Date: 2025-01-03 00:00:00
Tasks: Cantilever Beam, Sensitivity

Working from an observability characterization based on output energy sensitivity to changes in initial conditions, we derive both analytical and empirical observability Gramian tools for a class of continuum material systems. Using these results, optimal sensor placement is calculated for an Euler-Bernoulli cantilever beam for the following cases: analytical observability for the continuum system and analytical observability for a finite number of modes. Error covariance of an Unscented Kalman Filter is determined for both cases and compared to randomly placed sensors to demonstrate effectiveness of the techniques.