Gray-box approach to fault diagnosis of dynamical systems
Model-based fault diagnosis has become an important approach for diagnosis of dynamical systems.
fault diagnosis dynamical systems↗
SEARCH · Engineering Papers
Results for “dynamic system”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Data-Driven Distributed Algorithms for Estimating Eigenvalues and Eigenvectors of Interconnected Dynamical Systems
Here, the paper presents data-driven algorithms to estimate in a distributed manner the eigenvalues, right and left eigenvectors of an unknown linear (or linearized) interconnected dynamic system. In particular, the proposed algorithms do not require the identification of the system model in advance before performing the estimation. As a first step, we consider interconnected dynamical system with distinct eigenvalues. The proposed strategy first estimates the eigenvalues using the well-known Prony method. The right and left eigenvectors are then estimated by solving distributively a set of linear equations. One important feature of the proposed algorithms is that the topology of communication network used to perform the distributed estimation can be chosen arbitrarily, given that it is connected, and is also independent of the structure or sparsity of the system (state) matrix. The proposed distributed algorithms are demonstrated via a numerical example.
97 MATHEMATICS AND COMPUTING↗
Utilizing CellBox to Describe Varied Dynamical Systems
CellBox is a hybrid modeling framework that integrates machine-learning approaches with explicit mathematical modeling to determine the behavior of dynamical systems, intended for determining the complex interactions of molecule and phenotype within a cellular environment using perturbation/response-based data. The original work utilized analysis of a melanoma cell line, SK-Mel-133, which we sought to expand to and evaluate effectiveness in describing other nonlinear systems both within and outside of biology. We evaluated with two models. One model is based upon the free-fall of an object under a velocity-dependent drag force; this produced inherent perturbation/response data. The other model is based upon a form of mass-action molecular kinetics; for this, we ran the simulation to steady state in each species for each perturbation and select the steady state as input for CellBox. We determined that CellBox, outside of its original use case, can still strongly predict even non-biological dynamical systems in the small-perturbation regime, with r = 0.99977 to 0.85123, p < 0.05 for freefall. However, CellBox cannot accurately predict behavior within large-perturbation regimes, p >> 0.05 for freefall. In addition, we performed a naïve comparison of CellBox network structure to known network structure in the mass-action model to assess accuracy.
97 MATHEMATICS AND COMPUTING↗
Invariant subspaces and the controllability and observability of linear dynamical systems.
Invariant subspaces, controllability and observability of linear dynamic systems
Ford, D. A.↗
A method for the Liapunov stability analysis of hybrid dynamical systems possessing ignorable coordinates
Liapunov stability analysis of dynamic systems described by simultaneous ordinary and partial differential equations of motion, applying to satellite spin stabilization
Meirovitch, L.↗
Reachable sets for linear dynamical systems.
The properties of reachable sets for linear dynamical systems for specified control sets are discussed. Iterative procedures for determining numerical approximations of the reachable set are suggested and methods of obtaining an admissible control function which transfers an initial state to as near a prescribed target as possible is described. The problem of reachability with multiple control constraints is discussed and certain aspects of reachability for time-invariant systems with adjustable parameters is considered.
Pecsvaradi, T.↗
Uncertain dynamical systems: A differential game approach
A class of dynamical systems in a conflict situation is formulated and discussed, and the formulation is applied to the study of an important class of systems in the presence of uncertainty. The uncertainty is deterministic and the only assumption is that its value belongs to a known compact set. Asymptotic stability is fully discussed with application to variable structure and model reference control systems.
Gutman, S.↗
Analysis of dynamic systems with DAP4H computer program
Dynamic Analysis Program, FORTRAN 4 Level H /DAP4H/, developed from 27 subprograms, features liberal use of the subroutines, subprograms, and skeletonization to minimize programming effort in formulating models of new systems and components. It formulates mathematical models of complex mechanical, pneumatic, and hydraulic dynamic systems.
Absalom, J. G.↗
An approximate method for determining response of nonlinear dynamic systems to random disturbances
Approximation method for determining response of nonlinear dynamic systems to random disturbances
DYNAMIC RESPONSE↗
Optimal mitigation and control over power system dynamics for stochastic grid resilience
Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.
30 DIRECT ENERGY CONVERSION↗
A multi-scale temperature-based strategy to map hydrologic exchange flows in highly dynamic systems
Mapping and quantifying hydrologic exchange flows (HEFs) is critical to environmental monitoring and remediation at contaminated sites; however, these objectives are challenging in highly dynamic systems, e.g., along dam-regulated rivers, where HEFs vary rapidly. Direct seepage measurements are labor-intensive and difficult to automate, whereas indirect (e.g., thermal) and remote sensing methods have potential to allow continuous monitoring with limited field effort. We present a preliminary assessment of a multi-scale temperature-based strategy for monitoring HEFs along the Hanford Reach of the Columbia River, in eastern WA, United States. Five thermal methods were assessed. First, a vertical temperature profile (VTP) was installed into the streambed. The VTP data were analyzed using a data assimilation algorithm designed for automated real-time estimation in dynamic systems. Second, a thermal infrared (TIR) camera was used in roving surveys to identify seeps. Third, a TIR camera was stationed at the VTP site to collect images at 1-h intervals. Together, the two TIR datasets provided a basis to assess the potential for drone-based TIR. Fourth, temperature was measured at the sediment/water interface to assess fiber-optic distributed temperature sensing. Fifth, imagery from the ECOSTRESS satellite mission was acquired to assess the potential of spaceborne thermal monitoring. Based on our preliminary assessment, VTP, TIR, and bed temperature measurements provide complementary spatial coverage, temporal sampling, and resolution; these methods have potential for long-term, automated monitoring of HEFs. The publicly available spaceborne imagery, however, proved inadequate because of insufficient spatial resolution and data gaps resulting from cloud cover and revisit frequency.
54 ENVIRONMENTAL SCIENCES↗
Landsat Data Continuity Mission (LDCM) Flight Dynamics System (FDS)
The Landsat Data Continuity Mission (LDCM) will be launched in January 2013 to continue the legacy of Landsat land imagery collection that has been on-going for the past 40 years. While the overall mission and science goals are designed to produce the SAME data over the years, the ground systems designed to support the mission objectives have evolved immensely. The LDCM Flight Dynamics System (FDS) currently being tested and deployed for operations is highly automated and well integrated with the other ground system elements. The FDS encompasses the full suite of flight dynamics functional areas, including orbit and attitude determination and prediction, orbit and attitude maneuver planning and execution, and planning product generation. The integration of the orbit, attitude, maneuver, and products functions allows a very smooth flow for daily operations support with minimal input needed from the operator. The system also provides a valuable real-time component that monitors the on-board orbit and attitude during every ground contact and will autonomously alert the Flight Operations Team (FOT) personnel when any violations are found. This paper provides an overview of the LDCM Flight Dynamics System and a detailed description of how it is used to support space operations. For the first time on a Goddard Space Flight Center (GSFC)-managed mission, the ground attitude and orbits systems are fully integrated into a cohesive package. The executive engine of the FDS permits three levels of automation: low, medium, and high. The high-level, which will be the standard mode for LDCM, represents nearly lights-out operations. The paper provides an in-depth look at these processes within the FDS in support of LDCM in all mission phases.
Good, Susan M.↗
Cyber-Physical Dynamic System (CPDS) Modeling for Frequency Regulation and AGC Services of Distributed Energy Resources
The substantial integration of renewable energy brings significant challenges to balance the system in real time because of the variability and intermittency of renewable power. For the reliable system operation, the frequency regulation service is used to stabilize the system frequency through automatically balancing the system generation and load. On one hand, with the substantially increasing deployment of renewable energy in electricity system, the requirement of frequency regulation (FR) services increases significantly. On the other hand, the current main resource of FR services, the controllable conventional generation, is continuously decreasing in the system generation mix. This means that in the future high renewable penetration power system, additional and alternative reliable FR services providers such as distributed energy storage (DES) resources should be explored. Although the capability of utility-scale energy storage to provide FR services has been demonstrated, the integrated control and dynamic modeling of distributed energy resource (DER) providing frequency regulation grid services has been rarely explored. There are several challenges to adopt DERs to provide reliable grid services as illustrated in FERC 755. First, the distributed installation of DES requires a comprehensive cyber-physical dynamic system (CPDS) modeling to fully consider the impacts of the communication latency variability on its real time FR provision capability. Unlike the conventional generators, there are two-layer communication between DERs and system operators which increase the communication delay. Second, unlike the conventional generators whose dynamic models have been comprehensively studied, the difference among individual DER components' power-dynamic characteristic brings challenges in the accurate dynamic AGC modeling of its power-frequency relationship. Third, the temporal dependent state of charge uncertainty of DERs challenges DERs' power and frequency regulation capacities scheduling in the look-ahead generation scheduling. Therefore, the aggregator should optimize the frequency regulation provision from individual DER in real time. To overcome these challenges, this project proposes a cyber-physical dynamic system (CPDS) model to handle the uncertainty of DERs two-layer communication latency and power dynamics. The variability of DERs' communication delay and dynamic constraints will be comprehensively modeled. The DERs' AGC model with communication delay is designed to validate DESs' frequency regulation services. Like current performance-based frequency regulation evaluation, the delivery of DERs' frequency regulation will be assessed through post-analysis of the actual AGC response with respect to the AGC control signal from system operators. Consequently, the reliability improvement with DERs providing reliable frequency regulation services can be evaluated from a comprehensive perspective considering all the dynamics of communication and power.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Simulation process and data flow for a large system dynamics model
This paper documents the workflow and supporting technologies that a large system dynamics model, the biomass scenario model, employs to streamline the data preparation, simulation, quality control, and analysis process at the National Renewable Energy Laboratory. The workflow centers on automation of routine aspects of the flow of data between data stores, simulations, and visualizations. It enforces quality checks on data, reproducibility of computations, and traceability of results, while maintaining complete archives of modeling and analysis artifacts. The resulting frictionless simulation/analysis environment supports large-scale sensitivity analysis, interactive creation of ensembles of simulations, and rapid visualization-based exploration of simulation results.
09 BIOMASS FUELS↗
Consolidating the layout of rural settlements using system dynamics and the multi-agent system
Not Available
Huang, Qiang↗
Uncertainty Propagation in Dynamical Systems via Stochastic Collocation on Model Dynamics.
Abstract not provided.
De, Saibal↗
Parameter identifiability of linear dynamical systems
It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.
Glover, K.↗
Uncertainty Propagation in Dynamical Systems via Stochastic Collocation on Model Dynamics.
Abstract not provided.
De, Saibal↗