pwc-archive/papers-with-abstracts huggingface dataset:
Opinion formation in the world trade network
Authors: Célestin Coquidé, José Lages, Dima L. Shepelyansky
Date: 2024-01-04 00:00:00

We extend the opinion formation approach to probe the world influence of economical organizations. Our opinion formation model mimics a battle between currencies within the international trade network. Based on the United Nations Comtrade database, we construct the world trade network for the years of the last decade from 2010 to 2020. We consider different core groups constituted by countries preferring to trade in a specific currency. We will consider principally two core groups, namely, 5 Anglo-Saxon countries which prefer to trade in US dollar and the 11 BRICS+ which prefer to trade in a hypothetical currency, hereafter called BRI, pegged to their economies. We determine the trade currency preference of the other countries via a Monte Carlo process depending on the direct transactions between the countries. The results obtained in the frame of this mathematical model show that starting from year 2014 the majority of the world countries would have preferred to trade in BRI than USD. The Monte Carlo process reaches a steady state with 3 distinct groups: two groups of countries preferring, whatever is the initial distribution of the trade currency preferences, to trade, one in BRI and the other in USD, and a third group of countries swinging as a whole between USD and BRI depending on the initial distribution of the trade currency preferences. We also analyze the battle between USD, EUR and BRI, and present the reduced Google matrix description of the trade relations between the Anglo-Saxon countries and the BRICS+.
Learning of networked spreading models from noisy and incomplete data
Authors: Mateusz Wilinski, Andrey Y. Lokhov
Date: 2023-12-20 00:00:00
Tasks: Model Selection

Recent years have seen a lot of progress in algorithms for learning parameters of spreading dynamics from both full and partial data. Some of the remaining challenges include model selection under the scenarios of unknown network structure, noisy data, missing observations in time, as well as an efficient incorporation of prior information to minimize the number of samples required for an accurate learning. Here, we introduce a universal learning method based on scalable dynamic message-passing technique that addresses these challenges often encountered in real data. The algorithm leverages available prior knowledge on the model and on the data, and reconstructs both network structure and parameters of a spreading model. We show that a linear computational complexity of the method with the key model parameters makes the algorithm scalable to large network instances.
Secure Control of Connected and Automated Vehicles Using Trust-Aware Robust Event-Triggered Control Barrier Functions
Authors: H M Sabbir Ahmad, Ehsan Sabouni, Akua Dickson, Wei Xiao, Christos G. Cassandras, Wenchao Li
Date: 2024-01-04 00:00:00
Tasks: Navigate

We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to safely navigate through a conflict area (e.g., traffic intersections, merging roadways, roundabouts). Previous studies have shown that such a network can be targeted by adversarial attacks causing traffic jams or safety violations ending in collisions. We focus on attacks targeting the V2X communication network used to share vehicle data and consider as well uncertainties due to noise in sensor measurements and communication channels. To combat these, motivated by recent work on the safe control of CAVs, we propose a trust-aware robust event-triggered decentralized control and coordination framework that can provably guarantee safety. We maintain a trust metric for each vehicle in the network computed based on their behavior and used to balance the tradeoff between conservativeness (when deeming every vehicle as untrustworthy) and guaranteed safety and security. It is important to highlight that our framework is invariant to the specific choice of the trust framework. Based on this framework, we propose an attack detection and mitigation scheme which has twofold benefits: (i) the trust framework is immune to false positives, and (ii) it provably guarantees safety against false positive cases. We use extensive simulations (in SUMO and CARLA) to validate the theoretical guarantees and demonstrate the efficacy of our proposed scheme to detect and mitigate adversarial attacks.
Harnessing Membership Function Dynamics for Stability Analysis of T-S Fuzzy Systems
Authors: Donghwan Lee, Do-Wan Kim
Date: 2024-01-04 00:00:00

The main goal of this paper is to develop a new linear matrix inequality (LMI) condition for the asymptotic stability of continuous-time Takagi-Sugeno (T-S) fuzzy systems. A key advantage of this new condition is its independence from the bounds on the time-derivatives of the membership functions, a requirement present in the existing approaches. This is achieved by introducing a novel fuzzy Lyapunov function that incorporates an augmented state vector. Notably, this augmented state vector encompasses the membership functions, allowing the dynamics of these functions to be integrated into the proposed condition. This inclusion of additional information about the membership function serves to reduce the conservativeness of the suggested stability condition. To demonstrate the effectiveness of the proposed method, examples are provided.
A Pure Integral-Type PLL with a Damping Branch to Enhance the Stability of Grid-Tied Inverter under Weak Grids
Authors: Yi Zhou, Zhouchen Deng, Shi Chen, Yiwei Qiu, Tianlei Zang, Buxiang Zhou
Date: 2024-01-04 00:00:00

In a phase-locked loop (PLL) synchronized inverter, due to the strong nonlinear coupling between the PLL's parame-ters and the operation power angle, the equivalent damping coefficient will quickly deteriorate while the power angle is close to 90{\deg} under an ultra-weak grid, which causes the synchronous instability. To address this issue, in this letter, a pure integral-type phase-locked loop (IPLL) with a damping branch is proposed to replace the traditional PI-type PLL. The equivalent damping coefficient of an IPLL-synchronized inverter is decoupled with the steady-state power angle. As a result, the IPLL-synchronized inverter can stably operate under an ultra-weak grid when the equilibrium point exists. Finally, time-domain simulation results verify the effectiveness and correctness of the proposed IPLL.
Seamless Digital Engineering: A Grand Challenge Driven by Needs
Authors: James S. Wheaton, Daniel R. Herber
Date: 2024-01-04 00:00:00

Digital Engineering currently relies on costly and often bespoke integration of disparate software products to assemble the authoritative source of truth of the system-of-interest. Tools not originally designed to work together become an acknowledged system-of-systems, with their own separate feature roadmaps, deprecation, and support timelines. The resulting brittleness and conglomeration of disparate interfaces in the Digital Engineering Ecosystem of an organization drains resources and impairs efficiency and efficacy. If Model-Based Systems Engineering were applied to this problem, a complete system architecture model would be defined, and a purpose-built computing system-of-systems would be constructed to satisfy stakeholder needs. We have decades of research in computer science, cybersecurity, software and systems engineering, and human-computer interaction from which to draw that informs the design of a Seamless Digital Engineering tooling system, but it would require starting from a clean slate while carefully adopting existing standards. In this paper, this problem space and solution space are characterized, defining and identifying Seamless Digital Engineering as a grand challenge in Digital Engineering research.
Less Conservative Robust Reference Governors and Their Applications
Authors: Miguel Castroviejo-Fernandez, Huayi Li, Andrés Cotorruelo, Emanuele Garone, Ilya Kolmanovsky
Date: 2024-01-04 00:00:00
Tasks: State Estimation

The applications of reference governors to systems with unmeasured set-bounded disturbances can lead to conservative solutions. This conservatism can be reduced by estimating the disturbance from output measurements and canceling it in the nominal control law. In this paper, a reference governor based on such an approach is considered and time-varying, disturbance and state estimation errors bounding sets are derived. Consequently, the traditional implementation of a reference governor, which exploits a constraint admissible positively-invariant set of constant commands and initial states, is replaced by one which utilizes a time-dependent sequence of similar sets (which are not necessary nested). Examples are reported which include two applications to longitudinal control of aircraft that illustrate handling of elevator uncertainty and wing icing.
On Approximate Opacity of Stochastic Control Systems
Authors: Siyuan Liu, Xiang Yin, Dimos V. Dimarogonas, Majid Zamani
Date: 2024-01-03 00:00:00
Tasks: Relation

This paper investigates an important class of information-flow security property called opacity for stochastic control systems. Opacity captures whether a system's secret behavior (a subset of the system's behavior that is considered to be critical) can be kept from outside observers. Existing works on opacity for control systems only provide a binary characterization of the system's security level by determining whether the system is opaque or not. In this work, we introduce a quantifiable measure of opacity that considers the likelihood of satisfying opacity for stochastic control systems modeled as general Markov decision processes (gMDPs). We also propose verification methods tailored to the new notions of opacity for finite gMDPs by using value iteration techniques. Then, a new notion called approximate opacity-preserving stochastic simulation relation is proposed, which captures the distance between two systems' behaviors in terms of preserving opacity. Based on this new system relation, we show that one can verify opacity for stochastic control systems using their abstractions (modeled as finite gMDPs). We also discuss how to construct such abstractions for a class of gMDPs under certain stability conditions.
Integrated Cyber-Physical Resiliency for Power Grids under IoT-Enabled Dynamic Botnet Attacks
Authors: Yuhan Zhao, Juntao Chen, Quanyan Zhu
Date: 2024-01-03 00:00:00
Tasks: Decision Making

The wide adoption of Internet of Things (IoT)-enabled energy devices improves the quality of life, but simultaneously, it enlarges the attack surface of the power grid system. The adversary can gain illegitimate control of a large number of these devices and use them as a means to compromise the physical grid operation, a mechanism known as the IoT botnet attack. This paper aims to improve the resiliency of cyber-physical power grids to such attacks. Specifically, we use an epidemic model to understand the dynamic botnet formation, which facilitates the assessment of the cyber layer vulnerability of the grid. The attacker aims to exploit this vulnerability to enable a successful physical compromise, while the system operator's goal is to ensure a normal operation of the grid by mitigating cyber risks. We develop a cross-layer game-theoretic framework for strategic decision-making to enhance cyber-physical grid resiliency. The cyber-layer game guides the system operator on how to defend against the botnet attacker as the first layer of defense, while the dynamic game strategy at the physical layer further counteracts the adversarial behavior in real time for improved physical resilience. A number of case studies on the IEEE-39 bus system are used to corroborate the devised approach.
Physics-informed appliance signatures generator for energy disaggregation
Authors: Ilia Kamyshev, Sahar Moghimian Hoosh, Henni Ouerdane
Date: 2024-01-03 00:00:00

Energy disaggregation is a promising solution to access detailed information on energy consumption in a household, by itemizing its total energy consumption. However, in real-world applications, overfitting remains a challenging problem for data-driven disaggregation methods. First, the available real-world datasets are biased towards the most frequently used appliances. Second, both real and synthetic publicly-available datasets are limited in number of appliances, which may not be sufficient for a disaggregation algorithm to learn complex relations among different types of appliances and their states. To address the lack of appliance data, we propose two physics-informed data generators: one for high sampling rate signals (kHz) and another for low sampling rate signals (Hz). These generators rely on prior knowledge of the physics of appliance energy consumption, and are capable of simulating a virtually unlimited number of different appliances and their corresponding signatures for any time period. Both methods involve defining a mathematical model, selecting centroids corresponding to individual appliances, sampling model parameters around each centroid, and finally substituting the obtained parameters into the mathematical model. Additionally, by using Principal Component Analysis and Kullback-Leibler divergence, we demonstrate that our methods significantly outperform the previous approaches.
Development Of Impedance and Capacitance based Sensors for the Estimation of Adulterant Ingredients in Different Bio-Consumables
Authors: Chirantan Das
Date: 2024-01-03 00:00:00
Tasks: Unity

Electrical Impedance Spectroscopy (EIS) technique is found to be an excellent candidate for bio-sensing and food quality monitoring applications due to its rapid, robust, cost-effective and point-of-care approach. The present research work investigates the implementation of EIS technique supported by several optical spectroscopic techniques such as Ultraviolet-Visible (UV-Vis) and Fourier Transform Mid Infrared (FT-MIR) to detect and quantify several toxic adulterants in foods and bio-consumables. A comprehensive understanding on the background theory related to the study has been developed to analyze the overall polarization of the system and the effect of frequency on complex permittivity of such system have been observed. In the current work, the technique is applied to adulterated saccharides, honey and turmeric samples through a prototype sensing device. All the corresponding measurements have been performed by dipping a custom-made parallel plate conductivity cell with unity cell constant inside the solution under test. EIS study exhibited a steady variation of electrical parameters such as impedance, capacitance, conductance and current values with increasing adulterant percentage in the solution. Variation in such properties due to adulteration provides a systematic sensor plot through which one can determine their percentage of adulteration in unknown adulterated samples. Co-efficient of sensitivity has been extracted from the EIS data for adulteration study in terms of one of the measured parameters. The results of UV-Vis and FT-MIR studies have been used for comparative analyses which corroborate with the EIS results, wherever applicable.
Energy Sharing among Resources within Electrical Distribution Systems: A Systematic Review
Authors: G Hari Krishna, K. Victor Sam Moses Babu, Divyanshi Dwivedi, Pratyush Chakraborty, Pradeep Kumar Yemula, Mayukha Pal
Date: 2024-01-03 00:00:00
Tasks: energy trading

The rapid increase in Electric Vehicle (EV) adoption provides a promising solution for reducing carbon emissions and fossil fuel dependency in transportation systems. However, the increasing numbers of EVs pose significant challenges to the electrical grids. In addition, the number of Distributed Energy Resources (DER) and Microgrids (MGs) is increasing on a global scale to meet the energy demand, consequently changing the energy infrastructure. Recently, energy-sharing methods have been proposed to share excess energy from DERs and EVs in Electric Vehicle Charging Infrastructure (EVCI) and MGs. Accommodating this sharing mechanism with the existing electrical distribution systems is a critical issue concerning the economic, reliability, and resilience aspects. This study examines the ever-changing field of EVCI and the critical role of peer-to-peer (P2P) energy trading in mitigating the problems with grid management that result from unorganized EV charging and intermittency in DER. Also, the possibility of energy sharing in electrical distribution systems for microgrids and EVCI on various energy-sharing methods and algorithms are discussed in detail. Furthermore, the application of market clearing algorithms like game theory, double auction theory, blockchain technology, optimization techniques, machine learning algorithms, and other models from the existing literature are presented. This paper discusses the policies, economic benefits, environmental impacts, societal advantages, and challenges in distribution systems related to sharing in EVCI and MGs. A roadmap for future research and sharing strategies is provided to guide policymakers, researchers, and industry stakeholders toward a sustainable, resilient, and efficient energy market by integrating P2P technology into EVCIs and MGs.
Impact of DG and survey of pricing mechanism around different states in USA
Authors: Mohsen Abedi
Date: 2024-01-02 00:00:00

In this paper, we investigate the impact of the Distributed generation (DG) on Power Transmission Grid and pricing strategy for different geographical locations in different states, generally distributed generation (DG) on distribution feeders is known to have an impact on voltage regulation and power quality. A DG might provide voltage and power support in some cases, but most cases cause short term instability voltage, depending on the several variables, including relative DG size and location, power network and load character, so This paper also addressing to the following questions: the different between DG and conventional power station? What are penetration levels of different DG to the power grid and compliances to the IEEE relevant standards, discusses unexpected issues with a special emphasis on power protection coordination problems, potential advantage and disadvantage to using DG while Distributed Generation (DG) allows collection of energy from many sources and may provide lower environmental pollution then we will discuss what would be the main Factors affecting Electricity Prices of DG units at different states.
Linear-Quadratic Problems in Systems and Controls via Covariance Representations and Linear-Conic Duality: Finite-Horizon Case
Authors: Bassam Bamieh
Date: 2024-01-02 00:00:00
Tasks: LEMMA

Linear-Quadratic (LQ) problems that arise in systems and controls include the classical optimal control problems of the Linear Quadratic Regulator (LQR) in both its deterministic and stochastic forms, as well as $H^\infty$-analysis (the Bounded Real Lemma), the Positive Real Lemma, and general Integral Quadratic Constraints (IQCs) tests. We present a unified treatment of all of these problems using an approach which converts linear-quadratic problems to matrix-valued linear-linear problems with a positivity constraint. This is done through a system representation where the joint state/input covariance (the outer product in the deterministic case) matrix is the fundamental object. LQ problems then become infinite-dimensional semidefinite programs, and the key tool used is that of linear-conic duality. Linear Matrix Inequalities (LMIs) emerge naturally as conal constraints on dual problems. Riccati equations characterize extrema of these special LMIs, and therefore provide solutions to the dual problems. The state-feedback structure of all optimal signals in these problems emerge out of alignment (complementary slackness) conditions between primal and dual problems. Perhaps the new insight gained from this approach is that first LMIs, and then second, Riccati equations arise naturally in dual, rather than primal problems. Furthermore, while traditional LQ problems are set up in $L^2$ spaces of signals, their equivalent covariance-representation problems are most naturally set up in $L^1$ spaces of matrix-valued signals.
Identification of Additive Continuous-time Systems in Open and Closed loop
Authors: Rodrigo A. González, Koen Classens, Cristian R. Rojas, James S. Welsh, Tom Oomen
Date: 2024-01-02 00:00:00
Tasks: Additive models

When identifying electrical, mechanical, or biological systems, parametric continuous-time identification methods can lead to interpretable and parsimonious models when the model structure aligns with the physical properties of the system. Traditional linear system identification may not consider the most parsimonious model when relying solely on unfactored transfer functions, which typically result from standard direct approaches. This paper presents a novel identification method that delivers additive models for both open and closed-loop setups. The estimators that are derived are shown to be generically consistent, and can admit the identification of marginally stable additive systems. Numerical simulations show the efficacy of the proposed approach, and its performance in identifying a modal representation of a flexible beam is verified using experimental data.
Identification of Secondary Resonances of Nonlinear Systems using Phase-Locked Loop Testing
Authors: Tong Zhou, Gaetan Kerschen
Date: 2024-01-02 00:00:00

One unique feature of nonlinear dynamical systems is the existence of superharmonic and subharmonic resonances in addition to primary resonances. In this study, an effective vibration testing methodology is introduced for the experimental identification of these secondary resonances. The proposed method relies on phase-locked loop control combined with adaptive filters for online Fourier decomposition. To this end, the concept of a resonant phase lag is exploited to define the target phase lag to be followed during the experimental continuation process. The method is demonstrated using two systems featuring cubic nonlinearities, namely a numerical Duffing oscillator and a physical experiment comprising a clamped-clamped thin beam. The obtained results highlight that the control scheme can accurately characterize secondary resonances as well as track their backbone curves. A particularly salient feature of the developed algorithm is that, starting from the rest position, it facilitates an automatic and smooth dynamic state transfer toward one point of a subharmonic isolated branch, hence, inducing branch switching.