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At least 361 records · Page 20

Decentralized modular hybrid supervisory control for the formation of unmanned helicopters

Abstract Formation control of Unmanned Aerial Vehicles (UAVs) requires them to tightly cooperate to reach and keep the formation, while avoiding collision. This paper proposes a novel decentralized hybrid supervisory control approach for the formation control of multiple UAVs. This is achieved by developing a symbolic motion planning technique to polarly partition the motion space resulting in a finite state discrete event model for the motion dynamics of each UAV. Then, a modular discrete supervisor is designed for different components of the formation mission including reaching the formation, keeping the formation, and collision avoidance. Further, for the collision avoidance mechanism, a novel top‐down decomposition‐based approach is developed to design local supervisors decentralizedly. It is formally proved that with the proposed top‐down decomposition‐based approach, the (locally) supervised UAVs, as a whole, can cooperatively satisfy the desired (global) collision avoidance specification. The proposed decentralized supervisory control algorithm is also verified through a hardware‐in‐the‐loop simulator for the formation control of unmanned helicopters.

Karimoddini, Ali↗

Simulating the Impact of Dynamic Rerouting on Metropolitan-scale Traffic Systems

The rapid introduction of mobile navigation aides that use real-time road network information to suggest alternate routes to drivers is making it more difficult for researchers and government transportation agencies to understand and predict the dynamics of congested transportation systems. Computer simulation is a key capability for these organizations to analyze hypothetical scenarios; however, the complexity of transportation systems makes it challenging for them to simulate very large geographical regions, such as multi-city metropolitan areas. In this article, we describe enhancements to the Mobiliti parallel traffic simulator to model dynamic rerouting behavior with the addition of vehicle controller actors and vehicle-to-controller reroute requests. The simulator is designed to support distributed-memory parallel execution using discrete event simulation and be scalable on high-performance computing platforms. We demonstrate the potential of the simulator by analyzing the impact of varying the population penetration rate of dynamic rerouting on the San Francisco Bay Area road network. Using high-performance parallel computing, we can simulate a day in the San Francisco Bay Area with 19 million vehicle trips with 50 percent dynamic rerouting penetration over a road network with 0.5 million nodes and 1 million links in less than three minutes. We present a sensitivity study on the dynamic rerouting parameters, discuss the simulator’s parallel scalability, and analyze system-level impacts of changing the dynamic rerouting penetration. Furthermore, we examine the varying effects on different functional classes and geographical regions and present a validation of the simulation results compared to real-world data.

97 MATHEMATICS AND COMPUTING↗

Alfalfa

Alfalfa-based testbeds enable building equipment, control products, and workforce development tools to interact with dynamic building simulations representing the desired building, system, weather, and grid configuration. Alfalfa is used to de-risk implementation of load flexibility prior to field deployment, reducing the costs and timelines associated with adoption of decarbonization technology at the grid edge.

building energy modeling↗

A Cost-Effective Wave Energy Harvesting System with Maximum Power Point Tracking Capability

In this paper, we propose a low-cost bidirectional four-switch inverter that transfers three-phase energy between a permanent magnet synchronous generator (PMSG) driven by a wave energy collector and the power grid or a local ac load. To achieve high control performance, the machine-side inverter uses a high-gain observer for rotor position estimation and a Lyapunov-based approach for torque control. For the gridside inverter control, we estimate the filter capacitor voltage with a model reference adaptive system and control the dc-link voltage with a Lyapunov-based energy function. We also track the maximum power point from the sea waves with an integral control law that actively matches the generator impedance with that of the wave collection device. The proposed system supports both grid-following/forming modes. We validate our control design with simulation results on a 3-kW hardware setup.

wave energy, power systems integration, control de↗

Infrared-Fused Vision-Based Thermoregulation Performance Estimation for Personal Thermal Comfort-Driven HVAC System Controls

Thermal comfort is one of the primary factors influencing occupant health, well-being, and productivity in buildings. Existing thermal comfort systems require occupants to frequently communicate their comfort vote via a survey which is impractical as a long-term solution. Here, we present a novel thermal infrared-fused computer vision sensing method to capture thermoregulation performance in a non-intrusive and non-invasive manner. In this method, we align thermal and visible images, detect facial segments (i.e., nose, eyes, face boundary), and accordingly read the temperatures from the appropriate coordinates in the thermal image. We focus on the human face since it is often clearly visible to cameras and is not merged into a hot background (unlike hands). We use a regularized Gaussian Mixture model to track the thermoregulation changes over time and apply a heuristic algorithm to extract hot and cold indices. We present a personalized and a generalized comfort modeling method, selected based on the availability of the occupant historical indices measurements in a neutral environment, and use the time-series of the hot and cold indices to define corrections to HVAC system operations in the form of setpoint constraints. To evaluate the efficacy of our proposed approach in responding to thermal stimuli, we designed a series of controlled experiments to simulate exposure to cold and hot environments. While applying personalized modeling showed an acceptable average accuracy of 91.3%, the generalized model’s average accuracy was only 65.2%. This shows the importance of having access to physiological records in modeling and assessing comfort. We also found that individual differences should be considered in selecting the cooling and heating rates when some knowledge of the occupant’s overall thermal preference is available.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Numerical simulation projects in micromagnetics with Jupyter

We report a case study where an existing materials science course was modified to include numerical simulation projects on the micromagnetic behavior of materials. The Ubermag micromagnetic simulation software package is used in order to solve problems computationally. The simulation software is controlled through the Python code in Jupyter notebooks. Our experience is that the self-paced problem-solving nature of the project work can facilitate a better in-depth exploration of the course contents. We discuss which aspects of the Ubermag and the project Jupyter ecosystem have been beneficial for the students' learning experience and which could be transferred to similar teaching activities in other subject areas.

97 MATHEMATICS AND COMPUTING↗

Editorial: Edge computation and digital distribution networks

The development of digital technologies is penetrating all areas of energy revolution. Based on the in-depth integration of advanced digital technologies, distribution networks are gradually transforming into digital distribution networks (DDNs) with tremendous changes from the structure to the operation mode. DDNs is the digitalized appearance of the physical distribution network, in which ubiquitous connections and massive data are the basic characteristics (Huo et al., 2022). It is an important task to utilize the massive data and propose novel operation modes to construct more efficient and intelligent distribution networks (Jian et al., 2022). Among the advanced digital technologies in DDNs, edge computing has received wide attention (Zhao et al., 2022). It has superior performance in local sensing and intelligent computation, which can effectively relieve huge communication pressure. However, the limited computing resources and the complex computing tasks at the edge side significantly challenge the collaboration of distribution network regulation and advanced digital technologies (Hu et al., 2022). It is necessary to find out proper methods to utilize advanced digital technology to construct DDNs. This Research Topic is organized to introduce the recent progress in the construction, operation and advanced computational methods for DDNs. Finally, seven papers have been accepted, which can be sorted into the following three categories: 1) Evolution and technical features of DDNs, 2) Intelligent operation control of DDNs, 3) Advanced simulation for large-scale DDNs. The three sections below respectively introduce the major research and contributions of the papers covered in each category.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cooperative fault management for resilient integration of renewable energy

Cooperative fault management (CFM) is designed herein to control different types of renewable energy resources cooperatively during electrical faults. This paper studies systems with a high penetration of photovoltaic (PV) energy and wind energy. First, CFM leverages power converters of PV farms to boost the ride-through capability of nearby doubly-fed induction generators (DFIGs). By controlling PV farms’ output voltages to change smoothly during both fault initiation and fault clearance, the widely used crowbar in DFIGs is less likely to be activated. Crowbar activation adversely makes DFIGs lose controllability and absorb reactive power. The second contribution is the development of a software-defined CFM controller and a controller in-the-loop demonstration of the real-time performance of this optimization-based CFM. CFM capitalizes on distributed optimization formulation to enable flexibility, plug-and-play, and privacy-preserving. Computation time, however, is a major concern for optimization-based dynamics control. Here, real-time controller-in-the-loop simulation results show optimization-based CFM can output reference values around 60 ms and is quick enough for dynamic control.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

An adaptive model-free robotic force control strategy for hydrodynamic real-time hybrid simulation of floating offshore wind turbines

Real-time hybrid simulation (RTHS) - a cyber-physical testing approach - promises to enhance the simulation fidelity of the model-scale experiments used to prototype floating offshore wind turbines (FOWTs). In hydrodynamic RTHS (hydro-RTHS), actuators emulate aerodynamic forces on model-scale FOWT specimens subjected to physical waves in a hydrodynamic laboratory. Robotic arms are promising candidates for actuation in hydro-RTHS due to their compact multi-degree-of-freedom (DOF) capabilities. Unlike classical RTHS for seismic applications, which typically relies on displacement control, hydro-RTHS requires 6-DOF force control on newly designed floating prototypes in a model-scale setting, which presents significant challenges, including modeling uncertainties, directional asymmetry, configuration drift, bandwidth limitations, and time-varying delays. To mitigate these constraints without extensive pre-test calibration, this study proposes an adaptive model-free robotic force control strategy that combines task-space explicit force control with a secondary joint-space pose-keeping task. The Adaptive Feedforward Compensator (AFC) is integrated into the force control loop to compensate for time-varying delay. Experimental testing was conducted using a Franka Emika Panda robotic arm with a 1:50 scale FOWT specimen under operational wind and wave conditions. Results demonstrate stable and consistent 6-DOF force tracking. Effective delay compensation was observed, with low-frequency delay reductions ranging from 71.4% to 91.8% and improvements in low-frequency surge force tracking of 25.0% to 52.1%. This study enhances robotic actuation performance in hydro-RTHS and introduces a force control strategy that supports reliable robotic operation in uncertain floating environments. Future work will explore disturbance-observer mechanisms to further enhance wave rejection capabilities under extreme wind and wave conditions.

17 WIND ENERGY↗

Feedforward equilibrium trajectory optimization with GSPulse

One of the common tasks required for designing new plasma scenarios or evaluating capabilities of a tokamak is to design the desired equilibria using a Grad-Shafranov (GS) equilibrium solver. However, most standard equilibrium solvers are time-independent and do not include dynamic effects such as plasma current flux consumption, induced vessel currents, or voltage constraints. Another class of tools, plasma equilibrium evolution simulators, do include time-dependent effects. These are generally structured to solve the forward problem of evolving the plasma equilibrium given feedback-controlled voltages. In this work, we introduce GSPulse, a novel algorithm for equilibrium trajectory optimization, that is more akin to a pulse planner than a pulse simulator. GSPulse includes time-dependent effects and solves the inverse problem: given a user-specified set of target equilibrium shapes, as well as limits on the coil currents and voltages, the optimizer returns trajectories of the voltages, currents, and achievable equilibria. This task is useful for scoping performance of a tokamak and exploring the space of achievable pulses. The computed equilibria satisfy both Grad-Shafranov force balance and axisymmetric circuit dynamics. The optimization is performed by restructuring the free-boundary equilibrium evolution equations into a form where it is computationally efficient to optimize the entire dynamic sequence. GSPulse can solve for hundreds of equilibria simultaneously within a few minutes. GSPulse has been validated against NSTX-U and MAST-U experiments and against SPARC feedback control simulations, and is being used to perform scenario design for SPARC. The computed trajectories can be used as feedforward inputs that are connected to the feedback controller to inform and improve feedback performance. The code for GSPulse is available open-source at github.com/jwai-cfs/GSPulse_public.

equilibrium↗

Modular Isolated Soft-Switching Medium Voltage String Inverter for Large-Scale PV Farm

This paper presents a single-stage modular isolated soft-switching medium voltage string inverter (MVSI) with tri-port configuration to interconnect PV and storage to medium voltage (MV) grid. The modular MVSI provides advanced functionalities such as energy storage elements integration without additional converters, connection to MV grid resulting in lower distribution losses in the PV farm, high-frequency galvanic isolation, independent control of PV, storage and grid power, high modularity and scalability. The topology of the MVSI, operation principle and model-predictive priority-switching (MPPS) control to achieve fast dynamic balancing across stacked modules are discussed. The independent power control is validated in PLECS simulation and the operation of stacked MVSI with MPPS control is verified through Hardware-in-the-loop (HIL) simulation. Here, the hardware prototype of 25 kVA MVSI building block is developed. 18 kW experimental results of single building block verifying tri-ports operation and 20 kW experimental results of two modules stacked operation are presented. A clean sinusoidal waveform with negligibly low THD in both tests is obtained. A low dv/dt of <; 1kV/us and soft-switching are achieved.

30 DIRECT ENERGY CONVERSION↗

Load Mitigating Feedback Control of WECs

This report outlines the development of load-mitigating feedback control for wave energy converters. A simple, self-tuning multi-objective controller is demonstrated in simulation for a 3-DOF (surge, heave, pitch) point absorber. In previous work, the proposed control architecture has been shown to be effective in experiment for a variety of device archetypes for the single objective of the maximization of electrical power capture: here this architecture is extended to reduce device loading as well. In particular, PTO actuation forces and the minimization of fatigue damage (determined from the sum of wave-exerted and PTO forces) are considered as additional objectives for the self-tuning controller. This controller is demonstrated for two similar, but distinct systems: one described by the identified linear models from physical testing of the WaveBot device, and another based upon a WEC-Sim simulation that expands upon boundary element method data from the WaveBot device. In both cases, because the power surface is consistently fairly flat in the vicinity of control parameters that maximize power capture in contrasting sea-states, it is found to be generally possible to mitigate either fatigue damage or PTO load. However, PTO load is found to conflict with fatigue damage in some sea-states, limiting the efficacy of control objectives that attempt to mitigate both simultaneously. Additionally, coupling between the surge and pitch DOFs also limits the extent to which fatigue damage can be mitigated for both DOFs in some sea-states. Because control objectives can be considered a function of the sea-state (e.g., load mitigation may not be a concern until the sea is sufficiently large) a simple transition strategy is proposed and demonstrated. This transition strategy is found to be effective with some caveats: firstly, it cannot circumvent the aforementioned objective contradictions. Secondly, this objective transition is too slow to act as a system constraint, and objective thresholds must thus be considered quite conservatively. Improvement of the adjustment strategy is demonstrated through the addition of an integral term. Selection of well-performing transition parameters can be a function of sea-state. While a simple selection procedure is proposed, it is non-optimal, and a more robust selection procedure is suggested for future work.

16 TIDAL AND WAVE POWER↗

Orographic enhancement of rainfall over the Congo Basin

Abstract The Congo rainforest located in central equatorial Africa is an important, yet understudied part of the globe surrounded by complex orographic features. A primitive understanding of precipitation processes such as mesoscale convective dynamics magnifies uncertainties in the future climate projections of the hydrological cycle over the Congo. Furthermore, the effects of orography, which is an important forcing for convection and precipitation, are poorly resolved by climate models, and ill‐conceptualized over the Congo. To address this knowledge gap, perturbed orographic forcing experiments are conducted using the Weather Research and Forecasting (WRF) mesoscale numerical model in a high‐resolution convection‐permitting model setup. The model simulated selected dates in November 2014. The thunderstorms and rainfall simulated in the control run for the case study analyzed in this article compared reasonably well to satellite‐derived brightness temperature and rainfall data. The results from this case study show that the dynamical impact of increasing the height of the East African Highlands is the blocking of the lower‐tropospheric tropical easterlies. This weakening of the lower‐tropospheric zonal winds increases the windshear over the Congo Basin resulting in slower propagating, more intense mesoscale convective systems with enhanced rainfall.

54 ENVIRONMENTAL SCIENCES↗

Modeling Riverine Dissolved and Particulate Organic Carbon Fluxes from Two Small Watersheds in the Northeastern United States

The coupled carbon (C) cycle across terrestrial and aquatic environments at the watershed scale has been identified as an important, but poorly constrained component of the global carbon budget. Here, we extended Soil and Water Assessment Tool (SWAT) with coupled riverine particulate organic carbon (POC) and dissolved organic carbon (DOC) modules (referred to as SWAT-C hereafter). Results show that SWAT-C reproduced daily POC and DOC fluxes well in two watersheds in the Northeastern United States. We found that SWAT-C tended to underestimate high flows and peak DOC and POC fluxes. Uncertainty analysis indicated flux uncertainties associated with POC and DOC simulation were larger than those for flow simulation. Sensitive parameters controlling POC and DOC biogeochemical processes were identified along with how these parameters influence mechanisms underlying C cycling. We anticipate that the tool developed and applied here will inform C related ecosystem services in watershed assessment and planning.

Dissolved organic carbon, Particulate organic carb↗

Improving Resilience of Bus Bunching Holding Strategy through a Rolling Horizon Approach

Providing public transportation with quality service is critical to attracting more passengers to the system. However, high-demand routes are prone to the so-called bus bunching -- a tendency of buses to group as a consequence of variations in travel times and demands. Bus holding is applied to overcome this effect. In this study, we present a novel method for bus holding in which the control law is based only on the buses' position using a computationally efficient rolling horizon approach. The method uses similar inputs as linear control approaches while not increasing significantly the computational time. However, the method overcomes key a weakness of the linear control approach thanks to the explicit constraint handling that always ensures the control action effectiveness. Simulation experiments in a validation case and a model-specific for a bus rapid transit line in Curitiba, Brazil showed a reduced holding time and improved resilience, delivering more than 20% reduction in delay time accounting for the on-board and station delays.

33 ADVANCED PROPULSION SYSTEMS↗

Biophysical principles of choanoflagellate self-organization

Inspired by the patterns of multicellularity in choanoflagellates, the closest living relatives of animals, we quantify the biophysical processes underlying the morphogenesis of rosette colonies in the choanoflagellate Salpingoeca rosetta . We find that rosettes reproducibly transition from an early stage of 2-dimensional (2D) growth to a later stage of 3D growth, despite the underlying variability of the cell lineages. Our perturbative experiments demonstrate the fundamental importance of a basally secreted extracellular matrix (ECM) for rosette morphogenesis and show that the interaction of the ECM with cells in the colony physically constrains the packing of proliferating cells and, thus, controls colony shape. Simulations of a biophysically inspired model that accounts for the size and shape of the individual cells, the fraction of ECM, and its stiffness relative to that of the cells suffices to explain our observations and yields a morphospace consistent with observations across a range of multicellular choanoflagellate colonies. Overall, our biophysical perspective on rosette development complements previous genetic perspectives and, thus, helps illuminate the interplay between cell biology and physics in regulating morphogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Design of the American Wake Experiment (AWAKEN) field campaign

The American WAKE experimeNt (AWAKEN) is a multi-institutional collaborative field campaign, starting in March 2022, that will gather an unprecedented data set including both atmospheric observations and wind plant operational data. This comprehensive data set will be used to characterize the wind plant performance and turbine loading in different operational and atmospheric conditions and validate the use of different wind plant control strategies and simulation frameworks. An extensive field campaign like AWAKEN requires proper coordination and long-term planning to be successful. In this paper, we review the major activities planned during AWAKEN to provide information for current and future project partners. Specifically, we provide information about the project sites, their planned instruments, and how these will relate to the scientific objectives of the overall AWAKEN project.

17 WIND ENERGY↗