Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “IDENTIFICATION SYSTEMS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

Hybrid Dynamic Modeling of Smart Inverter

This letter proposes a novel hybrid method for assessing grid-connected three-phase converter interfaced resources (CIR) dynamics with the IEEE standard 1547-2018 grid support functions (GSFs), which blends physics and data-driven techniques. First, the letter derives an analytical model of a CIR to represent the internal physics and data-driven model (DDM) using a system identification algorithm to represent the rest of the dynamics, including the GSF. The derived hybrid model combines the analytical model of CIR and DDM, which balances accuracy and flexibility and is compared with the detailed switched model. Furthermore, the efficacy of the proposed approach to represent the advanced CIR dynamics is substantiated by power hardware-in-the-loop experiment data where real measurements from a commercial CIR are used to cross-validate the proposed approach. Furthermore, the results indicate that despite simple, the hybrid model accurately reproduces the dynamics of the detailed CIR model with an acceptable accuracy.

Data-driven model↗

Reduced-Order Aerodynamic Modeling Based on CFD Frequency Responses from Multisine Inputs

A system identification analysis was performed to determine a reduced-order model (ROM) of a computational fluid dynamics (CFD) solver in support of linear aeroservoelastic model development and feedback control design. The approach was applied to the FUN3D code for the half-span wind tunnel test article used in the NASA-Boeing collaboration called the Integrated Adaptive Wing Technology Maturation (IAWTM) project. In a transonic flow condition, multiple inputs (11 structural mode displacements and 3 control surface deflections) were simultaneously excited with orthogonal phase-optimized multisines while multiple outputs (the corresponding 14 generalized aerodynamic forces) were recorded. From these recorded times series, the matrix of frequency responses was computed and subsequently fit using rational function approximations (RFAs). It was found that the entire (14 x 14) matrix of frequency responses could be determined from a single CFD run and that results generally followed trends predicted using other methods. Differences were attributed to the modeling fidelity and nonlinearities from structural mode and control surface interactions at higher reduced frequencies. More accurate fits of the RFAs to the frequency response data were obtained by making two CFD runs, one with only structural mode excitations and one with only control surface excitations, which reduced the degree of nonlinearity in the modeling data.

Aeroservoelasticity↗

Physics vs structure: A systematic benchmark of learning strategies for multi-zone building thermal dynamics

Recent advances in physics-informed and data-driven machine learning promise improved thermal models for advanced building control, yet there is limited quantitative evidence on when added physics structure and architectural complexity are beneficial. Here, this work presents a systematic benchmark of five representative system identification methods for modeling multi-zone building thermal dynamics: linear state-space models, multi-layer perceptrons, neural state-space models, neural ordinary differential equations, and physically-consistent neural networks. The methods are evaluated across multiple data regimes and zone coupling strategies. Using a high-fidelity multi-zone commercial building emulator, we examine short-term and long-term prediction accuracy, computational efficiency, and ease of development. Our results reveal critical trade-offs between prediction performance, model complexity, and physical consistency. We demonstrate that decoupled, nonlinear black-box models consistently outperform coupled physics-constrained architectures in both predictive accuracy and out-of-distribution robustness in majority of the test cases for the building type considered in the study. Our findings quantify the cost of complexity in building thermal modeling and provide concrete, actionable, scenario-based guidelines for selecting model classes for control-oriented applications.

Building thermal modeling↗

On the problem of modeling for parameter identification in distributed structures

Structures are often characterized by parameters, such as mass and stiffness, that are spatially distributed. Parameter identification of distributed structures is subject to many of the difficulties involved in the modeling problem, and the choice of the model can greatly affect the results of the parameter identification process. Analogously to control spillover in the control of distributed-parameter systems, identification spillover is shown to exist as well and its effect is to degrade the parameter estimates. Moreover, as in modeling by the Rayleigh-Ritz method, it is shown that, for a Rayleigh-Ritz type identification algorithm, an inclusion principle exists in the identification of distributed-parameter systems as well, so that the identified natural frequencies approach the actual natural frequencies monotonically from above.

Norris, Mark A.↗

A perturbation technique for parameter identification in distributed structures

Structures are often characterized by parameters, such as mass and stiffness, that are spatially distributed. Parameter identification of distributed structures is subject to many of the difficulties involved in the modeling problem, and the choice of the model can greatly affect the results of the parameter identification process. Analogously to control spillover in the control of distributed-parameter systems, identification spillover is shown to exist as well and its effect is to degrade the parameter estimates. Moreover, as in modeling by the Rayleigh-Ritz method, it is shown that, for a Rayleigh-Ritz type identification algorithm, an inclusion principle exists in the identification of distributed-parameter systems as well, so that the identified natural frequencies approach the actual natural frequencies monotonically from above.

Meirovitch, L.↗

On the problem of modeling for parameter identification in distributed structures

Structures are often characterized by parameters, such as mass and stiffness, that are spatially distributed. Parameter identification of distributed structures is subject to many of the difficulties involved in the modeling problem, and the choice of the model can greatly affect the results of the parameter identification process. Analogously to control spillover in the control of distributed-parameter systems, identification spillover is shown to exist as well and its effect is to degrade the parameter estimates. Moreover, as in modeling by the Rayleigh-Ritz method, it is shown that, for a Rayleigh-Ritz type identification algorithm, an inclusion principle exists in the identification of distributed-parameter systems as well, so that the identified natural frequencies approach the actual natural frequencies monotonically from above.

Norris, Mark A.↗

Real-time reconstruction and control of pedestal-top electron density using RMP and gas puff at KSTAR

We report the experimental results of controlling the pedestal-top electron density by applying resonant magnetic perturbation (RMP) with in-vessel control coils and the main gas puff in the 2024-2025 KSTAR experimental campaign. The density is reconstructed using a parameterized $ψ_N$ grid and five channels of line-averaged density measured by the two-colored interferometer (TCI). The reconstruction procedure is accelerated by deploying a multi-layer perceptron to run in approximately 120 µ s and is sufficiently fast for real-time control. A proportional-integral controller was adopted, with the controller gains estimated from the system identification procedure. The experimental results demonstrate that the developed controller can follow a dynamic target while exclusively using both actuators. The absolute percentage errors between the electron density at $ψ_N$ = 0.89 and the target were approximately 1.5% median and a 2.5% average, respectively. The developed controller can even lower the density by using the pump-out mechanism under RMP, and it can follow a more dynamic range of density targets than a single actuator controller. The developed controller will enable experimental scenario exploration within a shot by dynamically setting the density target or maintaining a constant electron density within a discharge.

EFIT↗

Performance evaluation capabilities for the design of physical systems

The results are presented of a study aimed at developing and formulating a capability for the limiting performance of large steady state systems. The accomplishments reported include: (1) development of a theory of limiting performance of large systems subject to steady state inputs; (2) application and modification of PERFORM, the computational capability for the limiting performance of systems with transient inputs; and (3) demonstration that use of an inherently smooth control force for a limiting performance calculation improves the system identification phase of the design process for physical systems subjected to transient loading.

Pilkey, W. D.↗

NASA Low Visibility Landing and Surface Operations (LVLASO) Atlanta Demonstration: Surveillance Systems Performance Analysis

NASA conducted a series of flight experiments at Hartsfield Atlanta International Airport as part of the Low Visibility Landing and Surface Operations (LVLASO) Program. LVLASO is one of the subelements of the NASA Terminal Area Productivity (TAP) Program, which is focused on providing technology and operating procedures for achieving clear-weather airport capacity in instrument-weather conditions, while also improving safety. LVLASO is investigating various technologies to be applied to airport surface operations, including advanced flight deck displays and surveillance systems. The purpose of this report is to document the performance of the surveillance systems tested as part of the LVLASO flight experiment. There were three surveillance sensors tested: primary radar using Airport Surface Detection Equipment (ASDE-3) and the Airport Movement Area Safety System (AMASS), Multilateration using the Airport Surface Target Identification System (ATIDS), and Automatic Dependent Surveillance - Broadcast (ADS-B) operating at 1090 MHz. The performance was compared to the draft requirements of the ICAO Advanced Surface Movement Guidance and Control System (A-SMGCS). Performance parameters evaluated included coverage, position accuracy, and update rate. Each of the sensors was evaluated as a stand alone surveillance system.

Cassell, Rick↗

MRDIS Case Study

The Mobile Radiation Detection and Identification System (MRDIS) is a large mobile scanner that inspects containers in transit from cargo ships for radiological materials. The MRDIS platform operates as a two-part system with one MRDIS using a plastic Polyvinyl Toleune (synthetic polymer) for primary detection and another MRDIS that uses spectroscopic detectors for secondary isotopic identification. MRDIS can operate either independently or as part of a team, depending on the needs of the port. MRDIS is controlled by a human operator, who searches the computer monitor for any traces of radiological materials when the containers pass through the center of the system. Each MRDIS can also feed data into a central system or collect data on its own for additional material analysis. The system integrates radiation detection, radioisotope identification, an optical character recognition system, occupancy/speed sensors, wireless communications, and data processing capabilities to discern what specific radiological materials are of particular interest. In addition, Sandia engineers created a detailed set of requirements for subsequent models, allowing for faster implementation of additional detection systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Discrete approximation methods for parameter identification in delay systems

Approximation schemes for parameter identification problems in which the governing state equation is a linear functional differential equation of retarded type are constructed. The basis of the schemes is the replacement of the parameter identification problem having an infinite dimensional state equation by a sequence of approximating parameter identification problems in which the states are given by finite dimensional discrete difference equations. The difference equations are constructed using linear semigroup theory and rational function approximations to the exponential. Sufficient conditions are given for the convergence of solutions to the approximating problems, which can be obtained using conventional methods, to solutions to the original parameter identification problem. Finite difference and spline based schemes using Paderational function approximations to the exponential are constructed, and shown to satisfy the sufficient conditions for convergence. A discussion and analysis of numerical results obtained through the application of the schemes to several examples is included.

Rosen, I. G.↗

Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition

Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.

Hanson, Joshua↗

Nonparametric identification experiment

The following constitutes a summary of this paper: on-orbit identification methodology starts with nonparametric techniques for a priori system identification; development of the nonparametric identification and model determination experiment software has been completed; the validation experiments to be performed on the JPL Control and Identification Technology Validation Laboratory have been designed.

Yam, Yeung↗

An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.

Non-NASA Center↗

Commercially Hosted Government Payloads: Lessons from Recent Programs

In a commercially hosted operational mode, a scientific instrument or operational device is attached to a spacecraft but operates independently from the spacecraft s primary mission. Despite the expected benefits of this arrangement, there are few examples of hosted payload programs actually being executed by government organizations. The lack of hosted payload programs is largely driven by programmatic challenges, both real and perceived, rather than by technical challenges. Partly for these reasons, NASA has not sponsored a hosted payload program, in spite of the benefits and visible community interest in doing so. In the interest of increasing the use of hosted payloads across the space community, this paper seeks to alleviate concerns about hosted payloads by identifying these programmatic challenges and presenting ways in which they can be avoided or mitigated. Despite the challenges, several recent hosted payload programs have been successfully completed or are currently in progress. This paper presents an assessment of these programs, with a focus on acquisition, costs, schedules, risks, and other programmatic aspects. The hosted payloads included in this study are the Federal Aviation Administration's Wide Area Augmentation System (WAAS) payloads, United States Coast Guard's Automatic Identification System (AIS) demonstration payload, Department of Defense's IP Router In Space (IRIS) demonstration payload, the United States Air Force's Commercially Hosted Infrared Payload (CHIRP), and the Australian Defence Force's Ultra High Frequency (UHF) payload. General descriptions of each of these programs are presented along with issues that have been encountered and lessons learned from those experiences. A set of recommended approaches for future hosted payload programs is presented, with a focus on addressing risks or potential problem areas through smart and flexible contracting up front. This set of lessons and recommendations is broadly applicable to future hosted payload programs, whether they are technology demonstrations, communications systems, or operational sensors. Additionally, we present a basic cost model for commercial access to space for hosted payloads as a function of payload mass

Andraschko, Mark A.↗

Control optimization, stabilization and computer algorithms for aircraft applications

Computationally useful algorithms are considered that can aid the control engineer in designing systems control in linear time invariant dynamics for aircraft applications. Structural aspects of system identification, matrix parameterization, and the effect of feedback on identifiability of systems. Adaptive and stochastic control model constructions are projected, and a method for approximate identification of aircraft characteristics and subsequent generation of control signals is outlined.

Mitter, S. K.↗