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At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Model Predictive Control Tuning by Inverse Matching for a Wave Energy Converter

This paper investigates the application of a method to find the cost function or the weight matrices to be used in model predictive control (MPC) such that the MPC has the same performance as a predesigned linear controller in state-feedback form when constraints are not active. This is potentially useful when a successful linear controller already exists and it is necessary to incorporate the constraint-handling capabilities of MPC. This is the case for a wave energy converter (WEC), where the maximum power transfer law is well-understood. In addition to solutions based on numerical optimization, a simple analytical solution is also derived for cases with a short prediction horizon. These methods are applied for the control of an empirically-based WEC model. The results show that the MPC can be successfully tuned to follow an existing linear control law and to comply with both input and state constraints, such as actuator force and actuator stroke.

16 TIDAL AND WAVE POWER↗

NASA NTRS1990

Optimization of linear, controlled structures

An approach to the integrated design of linear controlled structures, which is being investigated as part of NASA's controlled structures interaction (CSI) methodology development program, is presented. The approach is integrated in the sense that the structure and its controller are simultaneously designed. The design methodology uses constrained nonlinear optimization procedures based on analytically obtained gradients of the structural responses. Design of the controller is based on the so-called Q-parameterization theory, which parameterizes all closed-loop input/output maps achievable with stabiizing linear controllers. Very general objective and constraint functions are possible, and structural shape can be included in the design variables. This method has been partially implemented and demonstrated; early findings are reported.

Hunziker, K. Scott↗

DOE OSTI2016

A robust approach to chance constrained optimal power flow with renewable generation

Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to operational constraints on generation and transmission assets. The uncertainty and variability of intermittent renewable generation is challenging current deterministic OPF approaches. Recent formulations of OPF use chance constraints to limit the risk from renewable generation uncertainty, however, these new approaches typically assume the probability distributions which characterize the uncertainty and variability are known exactly. We formulate a robust chance constrained (RCC) OPF that accounts for uncertainty in the parameters of these probability distributions by allowing them to be within an uncertainty set. The RCC OPF is solved using a cutting-plane algorithm that scales to large power systems. We demonstrate the RRC OPF on a modified model of the Bonneville Power Administration network, which includes 2209 buses and 176 controllable generators. In conclusion, deterministic, chance constrained (CC), and RCC OPF formulations are compared using several metrics including cost of generation, area control error, ramping of controllable generators, and occurrence of transmission line overloads as well as the respective computational performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1987

Structure-borne noise control for propeller aircraft

A laboratory test apparatus was developed which would allow the study and development of propeller wake/vortex-induced structure-borne interior noise control measures. Various methods of wing structural modification, including blocking masses, surface damping treatments, and tuned mechanical absorbers, were evaluated relative to reduced interior noise levels. Inboard wing fuel was found to act as an effective blocking mass. Wing panel add-on damping treatment in the form of a single, constrained layer was not an effective control measure, except in the area of the propeller wake. However, highly damped, tuned mechanical absorbers were found to be the most efficient structure-borne noise (SBN) control measure.

Unruh, James F.↗

DOE OSTI2026

Continental-Scale Controls on Hyporheic Respiration Revealed by Knowledge-Guided Machine Learning

Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.

Zheng, Jianqiu↗

DOE OSTI2026

Data driven drift correction for complex optical systems

To exploit the thousand-fold increase in spectral brightness of modern light sources, increasingly intricate experiments are being conducted that demand extremely precise beam trajectory. Maintaining the optimal trajectory over several hours of an experiment with the needed precision necessitates active drift control. Here, we outline time varying Bayesian optimization (TVBO) as a data driven approach for robust drift correction, and illustrate its application for a split and delay optical system composed of six crystals and twelve input dimensions. Using numerical simulations, we exhibit the application of TVBO for linear drift, non-smooth temporal drift as well as constrained TVBO for multi-objective control settings, representing real-life operating conditions. This approach can be easily adapted to other X-ray beam conditioning and guidance systems, including multi-crystal monochromators and grazing-incidence mirrors, to maintain sub-micrometer and nanoradian beam stability over the course of an experiment spanning several hours.

Bayesian optimization↗

NASA NTRS1988

Low authority-threshold control for large flexible structures

An improved active control strategy for the vibration control of large flexible structures is presented. A minimum force, low authority-threshold controller is developed to bring a system with or without known external disturbances back into an 'allowable' state manifold over a finite time interval. The concept of a constrained, or allowable feedback form of the controller is introduced that reflects practical hardware implementation concerns. The robustness properties of the control strategy are then assessed. Finally, examples are presented which highlight the key points made within the paper.

Zimmerman, D. C.↗

NASA NTRS2009

Orion Post-Landing Crew Thermal Control Modeling and Analysis Results

In a vehicle constrained by mass and power, it is necessary to ensure that during the process of reducing hardware mass and power that the health and well being of the crew is not compromised in the design process. To that end, it is necessary to ensure that in the final phase of flight - recovery, that the crew core body temperature remains below the crew cognitive deficit set by the Constellation program. This paper will describe the models used to calculate the thermal environment of the spacecraft after splashdown as well as the human thermal model used to calculate core body temperature. Then the results of these models will be examined to understand the key drivers for core body temperature. Finally, the analysis results will be used to show that additional cooling capability must be added to the vehicle to ensure crew member health post landing.

Cross, Cynthia D.↗

DOE OSTI2015

An Assessment of the Impact of Stochastic Day-Ahead SCUC on Economic and Reliability Metrics at Multiple Timescales

This paper incorporates the stochastic day-ahead security-constrained unit commitment (DASCUC) within a multi-timescale, multi-scheduling application with commitment, dispatch, and automatic generation control. The stochastic DASCUC is solved using a progressive hedging algorithm with constrained ordinal optimization to accelerate the individual scenario solution. Sensitivity studies are performed in the RTS-96 system, and the results show how this new scheduling application would impact costs and reliability with a closer representation of timescales of system operations in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1991

Sensitivity of Space Station alpha joint robust controller to structural modal parameter variations

The photovoltaic array sun tracking control system of Space Station Freedom is described. A synthesis procedure for determining optimized values of the design variables of the control system is developed using a constrained optimization technique. The synthesis is performed to provide a given level of stability margin, to achieve the most responsive tracking performance, and to meet other design requirements. Performance of the baseline design, which is synthesized using predicted structural characteristics, is discussed and the sensitivity of the stability margin is examined for variations of the frequencies, mode shapes and damping ratios of dominant structural modes. The design provides enough robustness to tolerate a sizeable error in the predicted modal parameters. A study was made of the sensitivity of performance indicators as the modal parameters of the dominant modes vary. The design variables are resynthesized for varying modal parameters in order to achieve the most responsive tracking performance while satisfying the design requirements. This procedure of reoptimization design parameters would be useful in improving the control system performance if accurate model data are provided.

Kumar, Renjith R.↗

NASA NTRS1989

Computational architecture for integrated controls and structures design

To facilitate the development of control structure interaction (CSI) design methodology, a computational architecture for interdisciplinary design of active structures is presented. The emphasis of the computational procedure is to exploit existing sparse matrix structural analysis techniques, in-core data transfer with control synthesis programs, and versatility in the optimization methodology to avoid unnecessary structural or control calculations. The architecture is designed such that all required structure, control and optimization analyses are performed within one program. Hence, the optimization strategy is not unduly constrained by cold starts of existing structural analysis and control synthesis packages.

Belvin, W. Keith↗

DOE OSTI2016

Using degrees of rate control to improve selective n-butane oxidation over model MOF-encapsulated catalysts: sterically-constrained Ag 3 Pd(111)

Metal nanoparticles encapsulated within metal organic frameworks (MOFs) offer steric restrictions near the catalytic metal that can improve selectivity, much like in enzymes. A microkinetic model is developed for the regio-selective oxidation of n -butane to 1-butanol with O 2 over a model for MOF-encapsulated bimetallic nanoparticles. The model consists of a Ag 3 Pd(111) surface decorated with a 2-atom-thick ring of (immobile) helium atoms which creates an artificial pore of similar size to that in common MOFs, which sterically constrains the adsorbed reaction intermediates. The kinetic parameters are based on energies calculated using density functional theory (DFT). The microkinetic model was analysed at 423 K to determine the dominant pathways and which species (adsorbed intermediates and transition states in the reaction mechanism) have energies that most sensitively affect the reaction rates to the different products, using degree-of-rate-control (DRC) analysis. This analysis revealed that activation of the C–H bond is assisted by adsorbed oxygen atoms, O*. Unfortunately, O* also abstracts H from adsorbed 1-butanol and butoxy as well, leading to butanal as the only significant product. This suggested to (1) add water to produce more OH*, thus inhibiting these undesired steps which produce OH*, and (2) eliminate most of the O 2 pressure to reduce the O* coverage, thus also inhibiting these steps. Combined with increasing butane pressure, this dramatically improved the 1-butanol selectivity (from 0 to 95%) and the rate (to 2 molecules per site per s). Moreover, 40% less O 2 was consumed per oxygen atom in the products. Under these conditions, a terminal H in butane is directly eliminated to the Pd site, and the resulting adsorbed butyl combines with OH* to give the desired 1-butanol. These results demonstrate that DRC analysis provides a powerful approach for optimizing catalytic process conditions, and that highly selectivity oxidation can sometimes be achieved by using a mixture of O 2 and H 2 O as the oxidant. This was further demonstrated by DRC analysis of a second microkinetic model based on a related but hypothetical catalyst, where the activation energies for two of the steps were modified.

catalysis (heterogeneous), materials and chemistry↗

DOE OSTI2014

Comparing Server Energy Use and Efficiency Using Small Sample Sizes

This report documents a demonstration that compared the energy consumption and efficiency of a limited sample size of server-type IT equipment from different manufacturers by measuring power at the server power supply power cords. The results are specific to the equipment and methods used. However, it is hoped that those responsible for IT equipment selection can used the methods described to choose models that optimize energy use efficiency. The demonstration was conducted in a data center at Lawrence Berkeley National Laboratory in Berkeley, California. It was performed with five servers of similar mechanical and electronic specifications; three from Intel and one each from Dell and Supermicro. Server IT equipment is constructed using commodity components, server manufacturer-designed assemblies, and control systems. Server compute efficiency is constrained by the commodity component specifications and integration requirements. The design freedom, outside of the commodity component constraints, provides room for the manufacturer to offer a product with competitive efficiency that meets market needs at a compelling price. A goal of the demonstration was to compare and quantify the server efficiency for three different brands. The efficiency is defined as the average compute rate (computations per unit of time) divided by the average energy consumption rate. The research team used an industry standard benchmark software package to provide a repeatable software load to obtain the compute rate and provide a variety of power consumption levels. Energy use when the servers were in an idle state (not providing computing work) were also measured. At high server compute loads, all brands, using the same key components (processors and memory), had similar results; therefore, from these results, it could not be concluded that one brand is more efficient than the other brands. The test results show that the power consumption variability caused by the key components as a group is similar to all other components as a group. However, some differences were observed. The Supermicro server used 27 percent more power at idle compared to the other brands. The Intel server had a power supply control feature called cold redundancy, and the data suggest that cold redundancy can provide energy savings at low power levels. Test and evaluation methods that might be used by others having limited resources for IT equipment evaluation are explained in the report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1976

Computational alternatives to obtain time optimal jet engine control

Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.

Basso, R. J.↗

DOE OSTI2020

Parallel Time Integration for Constrained Optimization

The number of transistors in an average processor continues to increase, but individual clock speeds have plateaued. Those transistors are instead going into additional cores, increasing the number of different things that a processor can do at once and placing an emphasis on parallel computation. Many problems in scientific computing follow a time-evolution model, and it can be difficult to solve such problems in parallel across the temporal domain. The Multi-Grid Reduction In Time (MGRIT) algorithm, developed at Lawrence Livermore National Laboratory (LLNL), solves differential equations with a method designed specifically to take advantage of extreme numbers of processors by parallelizing across time. The Tri-diagonal MGRIT (TriMGRIT) algorithm, also developed at LLNL, is a generalization of MGRIT which enables parallel-in-time solving of a greater number of problems. Constrained optimization problems, in particular, may be solved in parallel using TriMGRIT. These consist of choosing a control function such that an objective functional is minimized, constrained by a differential-equation. We consider two such problems: applying torque to a pendulum to bring it to a gentle stop and moving a crowd of people from one distribution into another. We also perform some miscellaneous theoretical and practical research, including investigating the use of a line-search subroutine to refine intermediate TriMGRIT results and preliminary work on strategies for choosing operators for TriMGRIT to use.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1977

Trajectory optimization for the Atlas/Centaur launch vehicle

A method for finding solutions to complex trajectory optimization problems with detailed hardware and launch vehicle constraints is presented. The trajectory optimization problem is formulated as a constrained function minimization problem by modeling the control by a function of a finite number of parameters. Although any parametric control model may be selected, the natural choice of parameters is the actual parameters of the parametric guidance equations flown on the flight digital computer. A variation of the method of multipliers is presented for performing the constrained function minimization. A functional is proposed that allows incorporation of state variable inequality constraints. Finally, optimization of the HEAO-A direct-ascent trajectory is discussed. The HEAO-A mission demonstrates profile optimization to meet range safety, tracking, heating, structural integrity, and attitude rate constraints.

Brusch, R. G.↗

DOE OSTI2023

Demonstrate FARM supervisory capabilities for a thermal energy storage problem for the DETAIL facility: IES Simulation Ecosystem Control System Development

The goal of the power dispatch problem for an Integrated Energy System (IES) is to adjust the power output and the heat flow of each component to maximize the profitability of the whole unit. Facilities that can integrate real-time digital signals, mock nuclear power, thermal energy storage and industrial heat use via high-temperature electrolysis were constructed at INL to support the research activities. The Dynamic Energy Technology and Integration Laboratory (DETAIL) houses the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET) and the Thermal Energy Distribution System (TEDS). In this report, the hierarchical control system architecture proposed in June 2023 milestone for the flexible operation of DETAIL facility is finalized and demonstrated. A brief description of the components and the corresponding Dymola models from the HYRBID repository is first provided. Then, the current control strategy is presented. In particular, the approach for generating the set-point trajectories to be fed to the PI controllers is analyzed, and its limits were identified. To preserve safe operation over both long-time and real-time horizons, the integration of a Supervisory Control layer embedding a modified version of FARM (Feasible Actuator Range Modifier) module is proposed. FARM is a component of the RAVEN-based FORCE framework designed to support HERON module at optimizing the operation of IES units. The proposed control system for DETAIL foresees FARM to be applied twice, i.e., the original version (“FARM-Validator”) aiding the solution of the power dispatch problem, and a modified version (“FARM-Supervisory”) coordinating the PID controllers. Despite the kernel of the two modules is the same, their tasks are quite different. The former intervenes at the beginning of each hour to prevent constraint violations over long time periods, the latter addresses real-time control tasks and monitors the response of constrained variables at a much finer time resolution. A tentative procedure for training the embedded Digital Twins with the experimental data is also proposed. Finally, the capabilities of the designed architecture and the impact of the added Supervisory Control layer are demonstrated by simulating a representative power dispatch scenario.

25 ENERGY STORAGE↗

NASA NTRS1996

Quality and Control of Water Vapor Winds

Water vapor imagery from the geostationary satellites such as GOES, Meteosat, and GMS provides synoptic views of dynamical events on a continual basis. Because the imagery represents a non-linear combination of mid- and upper-tropospheric thermodynamic parameters (three-dimensional variations in temperature and humidity), video loops of these image products provide enlightening views of regional flow fields, the movement of tropical and extratropical storm systems, the transfer of moisture between hemispheres and from the tropics to the mid- latitudes, and the dominance of high pressure systems over particular regions of the Earth. Despite the obvious larger scale features, the water vapor imagery contains significant image variability down to the single 8 km GOES pixel. These features can be quantitatively identified and tracked from one time to the next using various image processing techniques. Merrill et al. (1991), Hayden and Schmidt (1992), and Laurent (1993) have documented the operational procedures and capabilities of NOAA and ESOC to produce cloud and water vapor winds. These techniques employ standard correlation and template matching approaches to wind tracking and use qualitative and quantitative procedures to eliminate bad wind vectors from the wind data set. Techniques have also been developed to improve the quality of the operational winds though robust editing procedures (Hayden and Veldon 1991). These quality and control approaches have limitations, are often subjective, and constrain wind variability to be consistent with model derived wind fields. This paper describes research focused on the refinement of objective quality and control parameters for water vapor wind vector data sets. New quality and control measures are developed and employed to provide a more robust wind data set for climate analysis, data assimilation studies, as well as operational weather forecasting. The parameters are applicable to cloud-tracked winds as well with minor modifications. The improvement in winds through use of these new quality and control parameters is measured without the use of rawinsonde or modeled wind field data and compared with other approaches.

Jedlovec, Gary J.↗