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arXiv:2501.00480v1 Announce Type: new Abstract: This article presents fully distributed Lyapunov-based attack-resilient secondary control strategies for islanded inverter-based AC microgrids, designed to counter a broad spectrum of energy-unbounded False Data Injection (FDI) attacks, including exponential attacks, targeting control input channels. While distributed control improves scalability and reliability, it also increases susceptibility to cyber threats. The proposed strategies, supported by rigorous Lyapunov-based proofs, ensure uniformly ultimately bounded (UUB) convergence for frequency regulation, voltage containment, and power sharing, even under severe cyber attacks. The effectiveness of the proposed approach has been demonstrated through case studies on a modified IEEE 34-bus system, leveraging simulations and real-time Hardware-in-the-Loop experiments with OPAL-RT.

arXiv:2501.00856v1 Announce Type: new Abstract: Avionics systems of an Unmanned Aerial Vehicle (UAV) or drone are the critical electronic components found onboard that regulate, navigate, and control UAV travel while ensuring public safety. Contemporary UAV avionics work together to facilitate success of UAV missions by enabling stable communication, secure identification protocols, novel energy solutions, multi-sensor accurate perception and autonomous navigation, precise path planning, that guarantees collision avoidance, reliable trajectory control, and efficient data transfer within the UAV system. Moreover, special consideration must be given to electronic warfare threats prevention, detection, and mitigation, and the regulatory framework associated with UAV operations. This review presents the role and taxonomy of each UAV avionics system while covering shortcomings and benefits of available alternatives within each system. UAV communication systems, antennas, and location communication tracking are surveyed. Identification systems that respond to air-to-air or air-to-ground interrogating signals are presented. UAV classical and more innovative power sources are discussed. The rapid development of perception systems improves UAV autonomous navigation and control capabilities. The paper reviews common perception systems, navigation techniques, path planning approaches, obstacle avoidance methods, and tracking control. Modern electronic warfare uses advanced techniques and has to be counteracted by equally advanced methods to keep the public safe. Consequently, this work presents a detailed overview of common electronic warfare threats and state-of-the-art countermeasures and defensive aids. UAV safety occurrences are analyzed in the context of national regulatory framework and the certification process. Databus communication and standards for UAVs are reviewed as they enable efficient and fast real-time data transfer.

arXiv:2501.00262v1 Announce Type: new Abstract: As traditional large hydropower has been extensively exploited, micro-hydro systems have caught research increasing interest. New engineering challenges arise in developing micro-hydro systems in areas with significant elevation but prohibitive horizontal distances between primary reservoirs. This study addresses these challenges by proposing a cascade-pumped micro-hydro storage (CPMHS) system that leverages intermediate reservoirs to bridge long horizontal distances, enabling efficient energy transfer and storage. The methodology utilizes naturally occurring lakes with substantial head heights but limited feasibility for direct pumped storage due to horizontal separations. Integrating smaller, strategically placed intermediate reservoirs maximizes energy capture along the cascading path, making pumped storage viable in geographically constrained locations. The proposed system will enhance energy generation potential and provide additional benefits for water management. Using geographical data and a detailed case study focused on Mountain Lake and surrounding lakes, this paper demonstrates the energy efficiency and viability of cascade-based micro-hydro storage. A practical methodology for implementing CPMHS systems is proposed and validated by case studies. An optimization framework is developed for efficient energy capture in regions with challenging topography.

arXiv:2501.00476v1 Announce Type: new Abstract: This paper implies Bluetooth technology, which is put into effect to alter extant, wired into wireless Programmable Logic Controller (PLC). Here two Bluetooth devices are employed as a transceiver to transmit and receives the input signal to contrive wireless PLC. The main advantage of PLC is to control the output according to the status of input. In Bluetooth technology, the handshaking between the two Bluetooth modules takes place, which is interfaced with a microcontroller board (Arduino board) and then to PLC such that field devices can be controlled without wire.

arXiv:2501.00588v1 Announce Type: new Abstract: This paper introduces a novel, fully distributed control framework for DC microgrids, enhancing resilience against exponentially unbounded false data injection (EU-FDI) attacks. Our framework features a consensus-based secondary control for each converter, effectively addressing these advanced threats. To further safeguard sensitive operational data, a privacy-preserving mechanism is incorporated into the control design, ensuring that critical information remains secure even under adversarial conditions. Rigorous Lyapunov stability analysis confirms the framework's ability to maintain critical DC microgrid operations like voltage regulation and load sharing under EU-FDI threats. The framework's practicality is validated through hardware-in-the-loop experiments, demonstrating its enhanced resilience and robust privacy protection against the complex challenges posed by quick variant FDI attacks.

arXiv:2501.00739v1 Announce Type: new Abstract: Vertical take-off and landing (VTOL) aircraft pose a challenge in generating reference commands during transition flight. While sparsity between hover and cruise flight modes can be promoted for effective transitions by formulating $\ell_{1}$-norm minimization problems, solving these problems offline pointwise in time can lead to non-smooth reference commands, resulting in abrupt transitions. This study addresses this limitation by proposing a time-varying optimization method that explicitly considers time dependence. By leveraging a prediction-correction interior-point time-varying optimization framework, the proposed method solves an ordinary differential equation to update reference commands continuously over time, enabling smooth reference command generation in real time. Numerical simulations with a two-dimensional Lift+Cruise vehicle validate the effectiveness of the proposed method, demonstrating its ability to generate smooth reference commands online.

arXiv:2501.00167v1 Announce Type: new Abstract: This paper proposes a novel approach for designing functional observers for nonlinear systems, with linear error dynamics and assignable poles. Sufficient conditions for functional observability are first derived, leading to functional relationships between the Lie derivatives of the output to be estimated and the ones of the measured output. These are directly used in the proposed design of the functional observer. The functional observer is defined in differential input-output form, satisfying an appropriate invariance condition that emerges from the state-space invariance conditions of the literature. A concept of functional observer index is also proposed, to characterize the lowest feasible order of functional observer with pole assignment. Two chemical reactor applications are used to illustrate the proposed approach.

arXiv:2501.00249v1 Announce Type: new Abstract: This paper presents the development of "Control-Sync," a novel firmware for universal inverters in microgrids, designed to enhance grid stability and flexibility. As hybrid PV-battery systems become increasingly prevalent, there is a critical need for inverters capable of efficiently transitioning between grid-forming (GFM) and grid-following (GFL) modes. Our firmware introduces dual control paths that allow for seamless transitions without reliance on external control devices, reducing communication overhead and increasing operational reliability. Key features include direct phase-angle detection and frequency restoration capabilities, essential for managing asymmetrical power grids and dynamic load changes. The efficacy of Control-Sync is demonstrated through rigorous testing with grid emulators and multi-phase inverters, confirming its potential to improve microgrid reliability and efficiency. This study offers a scalable solution to enhance inverter adaptability in various grid conditions, fostering a more resilient energy infrastructure.

arXiv:2501.00421v1 Announce Type: new Abstract: We consider the problem of estimating the state transition matrix of a linear time-invariant (LTI) system, given access to multiple independent trajectories sampled from the system. Several recent papers have conducted a non-asymptotic analysis of this problem, relying crucially on the assumption that the process noise is either Gaussian or sub-Gaussian, i.e., "light-tailed". In sharp contrast, we work under a significantly weaker noise model, assuming nothing more than the existence of the fourth moment of the noise distribution. For this setting, we provide the first set of results demonstrating that one can obtain sample-complexity bounds for linear system identification that are nearly of the same order as under sub-Gaussian noise. To achieve such results, we develop a novel robust system identification algorithm that relies on constructing multiple weakly-concentrated estimators, and then boosting their performance using suitable tools from high-dimensional robust statistics. Interestingly, our analysis reveals how the kurtosis of the noise distribution, a measure of heavy-tailedness, affects the number of trajectories needed to achieve desired estimation error bounds. Finally, we show that our algorithm and analysis technique can be easily extended to account for scenarios where an adversary can arbitrarily corrupt a small fraction of the collected trajectory data. Our work takes the first steps towards building a robust statistical learning theory for control under non-ideal assumptions on the data-generating process.

arXiv:2501.00448v1 Announce Type: new Abstract: This paper proposes a novel control for Inverter-based Resources (IBRs) based on the Complex Frequency (CF) concept. The controller's objective is to maintain a constant CF of the voltage at the terminals of the IBR by adjusting its current reference. This current is imposed based on the well-known power flow equation, the dynamics of which are calculated through the estimation of the CF of the voltages of the adjacent buses. Performance is evaluated by analyzing local variations in frequency and magnitude of the voltage, as well as the response of the system's Center of Inertia (CoI) frequency, and then compared with conventional frequency droop, PI voltage controllers and virtual inertia. The case study utilizes the WSCC 9-bus system and a 1479-bus model of the Irish transmission grid and considers various contingencies and sensitivities such as the impact of limiters, delays, noise, R/X ratio, and EMT dynamics. Results show that the proposed scheme consistently outperforms the conventional controllers, leading to significant improvements in the overall dynamic response of the system.

arXiv:2501.00523v1 Announce Type: new Abstract: This paper introduces a novel approach for achieving fixed-time tracking consensus control in multiagent systems (MASs). Departing from the reliance on traditional controllers, our innovative controller integrates modified tuning and Lyapunov functions to guarantee stability and convergence. Furthermore, we have implemented an event-triggered strategy aimed at reducing the frequency of updates, alongside an output-feedback observer to manage unmeasured states effectively. To address the challenges posed by unknown functions and algebraic-loop problems, we opted for radial basis function neural networks (RBF NNs), chosen for their superior performance. Our methodology successfully mitigates Zeno's behavior and ensures stability within a narrowly defined set. The efficacy of our proposed solution is validated through two illustrative simulation examples.

arXiv:2501.00549v1 Announce Type: new Abstract: In this paper, we address the problem of timely delivery of status update packets in a real-time communication system, where a transmitter sends status updates generated by a source to a receiver over an unreliable channel. The timestamps of transmitted and received packets are measured using separate clocks located at the transmitter and receiver, respectively. To account for possible clock drift between these two clocks, we consider both deterministic and probabilistic drift scenarios. We analyze the system's performance regarding the Age of Information (AoI) and derive closed-form expressions for the distribution and the average AoI under both clock drift models. Additionally, we explore the impact of key system parameters on the average AoI through analytical and numerical results.

arXiv:2501.00657v1 Announce Type: new Abstract: Relative pose (position and orientation) estimation is an essential component of many robotics applications. Fiducial markers, such as the AprilTag visual fiducial system, yield a relative pose measurement from a single marker detection and provide a powerful tool for pose estimation. In this paper, we perform a Lie algebraic nonlinear observability analysis on a nonlinear dual quaternion system that is composed of a relative pose measurement model and a relative motion model. We prove that many common dual quaternion expressions yield Jacobian matrices with advantageous block structures and rank properties that are beneficial for analysis. We show that using a dual quaternion representation yields an observability matrix with a simple block triangular structure and satisfies the necessary full rank condition.

arXiv:2501.00722v1 Announce Type: new Abstract: For stabilizing stop-and-go oscillations in traffic flow by actuating a variable speed limit (VSL) at a downstream boundary of a freeway segment, we introduce event-triggered PDE backstepping designs employing the recent concept of performance-barrier event-triggered control (P-ETC). Our design is for linearized hyperbolic Aw-Rascle-Zhang (ARZ) PDEs governing traffic velocity and density. Compared to continuous feedback, ETC provides a piecewise-constant VSL commands-more likely to be obeyed by human drivers. Unlike the existing regular ETC (R-ETC), which enforces conservatively a strict decrease of a Lyapunov function, our performance-barrier (P-ETC) approach permits an increase, as long as the Lyapunov function remains below a performance barrier, resulting in fewer control updates than R-ETC. To relieve VSL from continuously monitoring the triggering function, we also develop periodic event-triggered (PETC) and self-triggered (STC) versions of both R-ETC and P-ETC. These are referred to as R/P-PETC and R/P-STC, respectively, and we show that they both guarantee Zeno-free behavior and exponential convergence in the spatial $L^2$ norm. With comparative simulations, we illustrate the benefits of the performance-barrier designs through traffic metrics (driver comfort, safety, travel time, fuel consumption). The proposed algorithms reduce discomfort nearly in half relative to driver behavior without VSL, while tripling the driver safety, measured by the average dwell time, relative to the R-ETC frequent-switching VSL schedule.

arXiv:2501.00051v1 Announce Type: new Abstract: Digital twin (DT) technology has emerged as a transformative approach to simulate, predict, and optimize the behavior of physical systems, with applications that span manufacturing, healthcare, climate science, and more. However, the development of DT models often faces challenges such as high data requirements, integration complexity, and limited adaptability to dynamic changes in physical systems. This paper presents a new method inspired by dynamic data-driven applications systems (DDDAS), called the dynamic data-driven generative of digital twins framework (DDD-GenDT), which combines the physical system with LLM, allowing LLM to act as DT to interact with the physical system operating status and generate the corresponding physical behaviors. We apply DDD-GenDT to the computer numerical control (CNC) machining process, and we use the spindle current measurement data in the NASA milling wear data set as an example to enable LLMs to forecast the physical behavior from historical data and interact with current observations. Experimental results show that in the zero-shot prediction setting, the LLM-based DT can adapt to the change in the system, and the average RMSE of the GPT-4 prediction is 0.479A, which is 4.79% of the maximum spindle motor current measurement of 10A, with little training data and instructions required. Furthermore, we analyze the performance of DDD-GenDT in this specific application and their potential to construct digital twins. We also discuss the limitations and challenges that may arise in practical implementations.

arXiv:2501.00110v1 Announce Type: new Abstract: Large-Scale Multi-Agent Systems (LS-MAS) consist of several autonomous components, interacting in a non-trivial way, so that the emerging behaviour of the ensemble depends on the individual dynamics of the components and their reciprocal interactions. These models can describe a rich variety of natural systems, as well as artificial ones, characterised by unparalleled scalability, robustness, and flexibility. Indeed, a crucial objective is devising efficient strategies to model and control the spatial behaviours of LS-MAS to achieve specific goals. However, the inherent complexity of these systems and the wide spectrum of their emerging behaviours pose significant challenges. The overarching goal of this thesis is, therefore, to advance methods for modelling, analyzing and controlling the spatial behaviours of LS-MAS, with applications to cellular populations and swarm robotics. The thesis begins with an overview of the existing Literature, and is then organized into two distinct parts. In the context of swarm robotics, Part I deals with distributed control algorithms to spatially organize agents on geometric patterns. The contribution is twofold, encompassing both the development of original control algorithms, and providing a novel formal analysis, which allows to guarantee the emergence of specific geometric patterns. In Part II, looking at the spatial behaviours of biological agents, experiments are carried out to study the movement of microorganisms and their response to light stimuli. This allows the derivation and parametrization of mathematical models that capture these behaviours, and pave the way for the development of innovative approaches for the spatial control of microorganisms. The results presented in the thesis were developed by leveraging formal analytical tools, simulations, and experiments, using innovative platforms and original computational frameworks.

arXiv:2501.00191v1 Announce Type: new Abstract: We study a networked economic system composed of $n$ producers supplying a single homogeneous good to a number of geographically separated markets and of a centralized authority, called the market maker. Producers compete \`a la Cournot, by choosing the quantities of good to supply to each market they have access to in order to maximize their profit. Every market is characterized by its inverse demand functions returning the unit price of the considered good as a function of the total available quantity. Markets are interconnected by a dispatch network through which quantities of the considered good can flow within finite capacity constraints. Such flows are determined by the market maker, who aims at maximizing a designated welfare function. We model such competition as a strategic game with $n+1$ players: the producers and the market game. For this game, we first establish the existence of Nash equilibria under standard concavity assumptions. We then identify sufficient conditions for the game to be potential with an essentially unique Nash equilibrium. Next, we present a general result that connects the optimal action of the market maker with the capacity constraints imposed on the network. For the commonly used Walrasian welfare, our finding proves a connection between capacity bottlenecks in the market network and the emergence of price differences between markets separated by saturated lines. This phenomenon is frequently observed in real-world scenarios, for instance in power networks. Finally, we validate the model with data from the Italian day-ahead electricity market.

arXiv:2501.00219v1 Announce Type: new Abstract: This paper investigates the potential of autonomous minibuses which take on-demand directional routes for pick-up and drop-off in a grid network of wider area with low density, followed by fixed routes in areas with demand. Mathematical formulation for generalized costs demonstrates its benefits, with indicators proposed to select existing bus routes for conversion with the options of zonal express and parallel routes. Simulations on modeled scenarios and case studies with bus routes in Chicago show reductions in both passenger costs and generalized costs over existing fixed-route bus service between suburban areas and CBD.

arXiv:2501.00390v1 Announce Type: new Abstract: In their seminal work, Gauci et al. (2014) studied the fundamental task of aggregation, wherein multiple robots need to gather without an a priori agreed-upon meeting location, using minimal hardware. That paper considered differential-drive robots that are memoryless and unable to compute. Moreover, the robots cannot communicate with one another and are only equipped with a simple sensor that determines whether another robot is directly in front of them. Despite those severe limitations, Gauci et al. introduced a controller and proved mathematically that it aggregates a system of two robots for any initial state. Unfortunately, for larger systems, the same controller aggregates empirically in many cases but not all. Thus, the question of whether a controller exists that aggregates for any number of robots remains open. In this paper, we show that no such controller exists by investigating the geometric structure of controllers. In addition, we disprove the aggregation proof of the paper above for two robots and present an alternative controller alongside a simple and rigorous aggregation proof.

arXiv:2501.00872v1 Announce Type: new Abstract: Existing data-driven control methods generally do not address False Data Injection (FDI) and Denial-of-Service (DoS) attacks simultaneously. This letter introduces a distributed data-driven attack-resilient consensus problem under both FDI and DoS attacks and proposes a data-driven consensus control framework, consisting of a group of comprehensive attack-resilient observers. The proposed group of observers is designed to estimate FDI attacks, external disturbances, and lumped disturbances, combined with a DoS attack compensation mechanism. A rigorous stability analysis of the approach is provided to ensure the boundedness of the distributed neighborhood estimation consensus error. The effectiveness of the approach is validated through numerical examples involving both leaderless consensus and leader-follower consensus, demonstrating significantly improved resilient performance compared to existing data-driven control approaches.