Search NASA⌕ Search

SEARCH · Search NASA

Results for “Model Predictive Control”

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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Recent Developments in the Radiation Belt Environment Model

The fluxes of energetic particles in the radiation belts are found to be strongly controlled by the solar wind conditions. In order to understand and predict the radiation particle intensities, we have developed a physics-based Radiation Belt Environment (RBE) model that considers the influences from the solar wind, ring current and plasmasphere. Recently, an improved calculation of wave-particle interactions has been incorporated. In particular, the model now includes cross diffusion in energy and pitch-angle. We find that the exclusion of cross diffusion could cause significant overestimation of electron flux enhancement during storm recovery. The RBE model is also connected to MHD fields so that the response of the radiation belts to fast variations in the global magnetosphere can be studied.Weare able to reproduce the rapid flux increase during a substorm dipolarization on 4 September 2008. The timing is much shorter than the time scale of wave associated acceleration.

Fok, M.-C.↗
DOE OSTI2024

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Abstract Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

25 ENERGY STORAGE↗
DOE OSTI2026

Evaluating the limitations of Bayesian metabolic control analysis

Bayesian Metabolic Control Analysis (BMCA) is a promising framework for inferring metabolic control coefficients in data-limited scenarios, combining Bayesian inference with linear-logarithmic (lin-log) rate laws. These metabolic control coefficients quantify how changes in enzyme activities affect steady-state fluxes and metabolite concentrations across a metabolic network. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCC), and concentration control coefficients (CCC) under varying data availability conditions using three synthetic metabolic network models. We demonstrate that BMCA predictions are highly dependent on the inclusion of flux and enzyme concentration data, with the omission of these datasets leading to severe inaccuracies. In our synthetic, enzyme-perturbation datasets, external metabolite concentrations had minimal impact and, in some cases, their exclusion improved predictions; when external-nutrient perturbations were introduced and those concentrations were observed, gains were at most modest. Additionally, we find that posterior estimation with both ADVI and HMC can underestimate large-magnitude elasticities in our synthetic settings, with ADVI showing somewhat higher variance under strong up-regulation; thus, recovering |elasticity| ≳ 1.5 remains challenging regardless of the inference engine. ADVI also fails to accurately infer allosteric interactions, even when regulatory effects are strong. While BMCA maintains reasonable accuracy in partially recovering the rankings of the highest FCC values, its estimates of absolute values remain constrained by prior assumptions and data limitations. Our findings reveal the BMCA algorithm’s strengths and weaknesses, providing guidance on its application in metabolic engineering, and highlighting the need for methodological refinements to enhance its predictive capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Dynamics and control of large space structures

An attempt is made to gather data useful to investigators in the fields of large space structure dynamics and control modeling, design and testing. Attention is given to structural dynamics and its relationship to such allied engineering fields as flutter analysis, as well as to problems in the prediction of atmospheric density at orbital altitude. The first challenge posed by large space structure control is the design of control systems with natural frequencies above several major structural frequencies. The establishment of a sufficiently accurate structural model, plant excitation, and shape maintenance, are noted to be additional problems.

Nurre, G. S.↗
NASA NTRS2005

A Model-based Approach to Controlling the ST-5 Constellation Lights-Out Using the GMSEC Message Bus and Simulink

Space Technology 5 (ST-5) is a three-satellite constellation, technology validation mission under the New Millennium Program at NASA to be launched in March 2006. One of the key technologies to be validated is a lights-out, model-based operations approach to be used for one week to control the ST-5 constellation with no manual intervention. The ground architecture features the GSFC Mission Services Evolution Center (GMSEC) middleware, which allows easy plugging in of software components and a standardized messaging protocol over a software bus. A predictive modeling tool built on MatLab's Simulink software package makes use of the GMSEC standard messaging protocol to interface to the Advanced Mission Planning System (AMPS) Scenario Scheduler which controls all activities, resource allocation and real-time re-profiling of constellation resources when non-nominal events occur. The key features of this system, which we refer to as the ST-5 Simulink system, are as follows: Original daily plan is checked to make sure that predicted resources needed are available by comparing the plan against the model. As the plan is run in real-time, the system re-profiles future activities in real-time if planned activities do not occur in the predicted timeframe or fashion. Alert messages are sent out on the GMSEC bus by the system if future predicted problems are detected. This will allow the Scenario Scheduler to correct the situation before the problem happens. The predictive model is evolved automatically over time via telemetry updates thus reducing the cost of implementing and maintaining the models by an order of magnitude from previous efforts at GSFC such as the model-based system built for MAP in the mid-1990's. This paper will describe the key features, lessons learned and implications for future missions once this system is successfully validated on-orbit in 2006.

Witt, Kenneth J.↗
NASA NTRS1990

Demand Assignment in the ACTS LBR System

On the Advanced Communications Technology Satellite (ACTS) being developed at NASA Lewis, low-burst-rate (LBR) traffic stations will access the ACTS multibeam package via two hopping beams that can be directed at certain areas in the continental U.S. An onboard baseband processor (BBP) demodulates uplink traffic, switches it between uplink and downlink beams at baseband, and then remodulates it for retransmission at 20 GHz. This study describes the demand-assigned operation of the ACTS LBR system, where the onboard switch is remote from both traffic stations and master control station (MCS). Network control uses inbound and outbound orderwire channels and a BBP control channel, allowing the MCS to coordinate assignment of individual 64-kb/s spacecraft channels. Models are developed to simulate the dynamics of the assignment process and verify the call blocking behavior, to predict control channel loads, and to evaluate algorithms for burst time plan rearrangement.

White, Lawrence W.↗
DOE OSTI2026

The Ponderomotive Effects of Narrow-band, Superconducting Resonators in Open and Closed Loop

In this work, we present measurements of ponderomotive instabilities in narrow-band, coaxial resonators in open and closed control loop systems. We show an analytical scheme we will use in future studies to examine the dependency of open loop stability on mechanical parameters. Analytical and simulation models are used to predict the onset of the oscillatory instability in half wave resonators with active disturbance rejection control for amplitude and phase stabilization. We demonstrate that for high amplitude controller bandwidths, ponderomotive oscillations can couple with the controller frequency response via higher harmonics and lower the threshold for the oscillatory instability. We reaffirm the superiority of in-phase/quadrature $(I/Q)$ component control in regards to preventing the oscillatory instability, and show how the phase controller can amplify the crosstalk of disturbances in amplitude and phase control. In cases with large disturbances, this effect can lead to instabilities not present in $I/Q$ control.

Brown, Jacob [Michigan State U.; Fermilab] (ORCID:↗
NASA NTRS2011

Predictive Models of Duration of Ground Delay Programs in New York Area Airports

Initially planned GDP duration often turns out to be an underestimate or an overestimate of the actual GDP duration. This, in turn, results in avoidable airborne or ground delays in the system. Therefore, better models of actual duration have the potential of reducing delays in the system. The overall objective of this study is to develop such models based on logs of GDPs. In a previous report, we described descriptive models of Ground Delay Programs. These models were defined in terms of initial planned duration and in terms of categorical variables. These descriptive models are good at characterizing the historical errors in planned GDP durations. This paper focuses on developing predictive models of GDP duration. Traffic Management Initiatives (TMI) are logged by Air Traffic Control facilities with The National Traffic Management Log (NTML) which is a single system for automated recoding, coordination, and distribution of relevant information about TMIs throughout the National Airspace System. (Brickman, 2004 Yuditsky, 2007) We use 2008-2009 GDP data from the NTML database for the study reported in this paper. NTML information about a GDP includes the initial specification, possibly one or more revisions, and the cancellation. In the next section, we describe general characteristics of Ground Delay Programs. In the third section, we develop models of actual duration. In the fourth section, we compare predictive performance of these models. The final section is a conclusion.

Kulkarni, Deepak↗
DOE OSTI2025

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom

Energy-efficient ventilation control plays an important role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate representations of indoor airflow, their high computational cost limits their use in real-time building control. In this work, we present a neural operator learning framework that combines the physical accuracy of CFD with the computational efficiency of machine learning to enable building ventilation control with the high-fidelity fluid dynamics models. Our method jointly optimizes the airflow supply rates and vent angles to reduce energy use and adhere to air quality constraints. We train an ensemble of neural operator transformer models to learn the mapping from building control actions to airflow fields using high-resolution CFD data. This learned neural operator is then embedded in an optimization-based control framework for building ventilation control. Experimental results show that our approach achieves significant energy savings compared to maximum airflow rate control, rule-based control, as well as data-driven control methods using spatially averaged CO 2 prediction and deep learning–based reduced-order models, while consistently maintaining safe indoor air quality. These results highlight the practicality and scalability of our method in maintaining energy efficiency and indoor air quality in real-world buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2018

ST7 Disturbance Reduction System (DRS) Colloid Micronewton Thruster Performance and Control Algorithm Model Simulation Validation in Flight

Colloid Micronewton Thrusters (CMNT) were flight demonstrated for the first time on the ST7Disturbance Reduction System (DRS) payload on the European Space Agency (ESA) Laser Interferometer Space Antenna (LISA) Pathfinder spacecraft for attitude and drag-free spacecraft control. LISA Pathfinder was a technology demonstration mission for ESA’s LISA gravitational wave observatory, currently in Phase A with a launch date of 2034. The DRS included the Integrated Avionics Unit (IAU), eight Colloid Micronewton Thrusters (CMNT), Dynamic Control Software (DCS) and Flight Software (FSW). The CMNT technology met performance requirements operating at 5-30 µN of thrust with ≤0.1 µN resolution and ≤0.1 µN/Hz thrust noise to deliver the required nanometer-level precision spacecraft control measured by the gravitational reference sensor (GRS) in the ESA LISA Technology Package (LTP). The performance of seven of the CMNT in flight was consistent with ground test results. The colloid thruster performance model of thrust and thrust noise as a function of operational parameters (i.e. beam current, voltage, temperature, etc.) was validated in flight over a wide range of conditions. A model and simulation of the thruster control algorithm was developed and validated with flight data to predict thrust noise. This capability is important because it is considered to be a significant source of position noise on the spacecraft and, therefore, the acceleration noise on the test masses, which provide the gravity wave measurements. The CMNT thruster model data and validation with LISA Pathfinder/ST7-DRS flight experiments are discussed in this paper.

Hruby, Vlad↗
NASA NTRS2015

Menstrual Cycle Control in Female Astronauts and the Associated Risk of Venous Thromboembolism

Venous thromboembolism (VTE) is a common and serious condition affecting approximately 1‐2 per 1000 people in the USA every year. There have been no documented case reports of VTE in female astronauts during spaceflight in the published literature. Some female astronauts use hormonal contraception to control their menstrual cycles and it is currently unknown how this affects their risk of VTE. Current terrestrial risk prediction models do not account for the spaceflight environment and the physiological changes associated with it. We therefore aim to estimate a specific risk score for female astronauts who are taking hormonal contraception for menstrual cycle control, to deduce whether they are at an elevated risk of VTE. A systematic review of the literature was conducted in order to identify and quantify known terrestrial risk factors for VTE. Studies involving analogues for the female astronaut population were also reviewed, for example, military personnel who use the oral contraceptive pill for menstrual suppression. Well known terrestrial risk factors, for example, obesity or smoking would not be applicable to our study population as these candidates would have been excluded during astronaut selection processes. Other risk factors for VTE include hormonal therapy, lower limb paralysis, physical inactivity, hyperhomocysteinemia, low methylfolate levels and minor injuries, all of which potentially apply to crew members LSAH data will be assessed to identify which of these risk factors are applicable to our astronaut population. Using known terrestrial risk data, an overall estimated risk of VTE for female astronauts using menstrual cycle control methods will therefore be calculated. We predict this will be higher than the general population but not significantly higher requiring thromboprophylaxis. This study attempts to delineate what is assumed to be true of our astronaut population, for example, they are known to be a healthy fit cohort of individuals, and combine physiological impacts of spaceflight (cephalic fluid shifts, lower limb inactivity) to understand specific risks associated with hormonal contraception.

Jain, Varsha↗
DOE OSTI2025

Self-consistent equilibrium and transport simulations for NSTX-U plasmas enhanced via machine learning surrogate models

The Control-Oriented Transport SIMulator (COTSIM) is an advanced equilibrium and transport code designed for simulating tokamak discharges at computational speeds suitable for control applications. COTSIM’s modular framework enables users to select models that balance accuracy with speed according to specific needs, allowing the code to operate from fast to faster-than-real-time performance levels. This work presents recent enhancements to COTSIM’s predictive accuracy for NSTX-U scenarios, achieved by integrating neural-network-based surrogate models and self-consistent equilibrium calculations. To improve source deposition predictions, a surrogate model for NUBEAM has been incorporated. Additionally, a surrogate model for the Multi-Mode Module (MMM) now supports predictions of anomalous thermal, momentum, and particle diffusivities—key factors for modeling the evolution of temperature and rotation. Each surrogate model was specifically trained for the NSTX-U operational regime to enhance COTSIM’s accuracy while maintaining computational efficiency. Moreover, COTSIM now couples fixed-boundary equilibrium solvers with its transport solvers, enabling self-consistent predictions of plasma profiles and equilibrium evolution over the discharge. Simulation results demonstrate strong agreement between COTSIM and TRANSP predictions for NSTX-U discharges. These substantial advancements expand COTSIM’s utility in model-based control applications for NSTX-U. Potential applications include simultaneous optimization of equilibrium and transport scenarios, integration into digital twins, real-time profile estimation (e.g., temperature and rotation) from limited or noisy measurements, and advanced feedback-based scenario control.

Equilibrium and transport modeling↗
NASA NTRS2010

Ares I Reaction Control System Propellant Feedline Decontamination Modeling

The objective of the work presented here is to quantify the effects of purge gas temperature, pressure, and mass flow rate on Hydrazine (Hz) decontamination rates of the Ares I Roll Control System and Reaction Control System. A survey of experts in this field revealed the absence of any decontamination rate prediction models. Three basic decontamination methods were identified for analysis and modeling. These include low pressure eduction, high flow rate purge, and pulse purge. For each method, an approach to predict the Hz mass transfer rate, as a function of system pressure, temperature, and purge gas mass flow rate, is developed based on the applicable physics. The models show that low pressure eduction is two orders of magnitude more effective than the high velocity purge, which in turn is two orders of magnitude more effective than the pure diffusion component of pulse purging of deadheads. Eduction subjects the system to low pressure conditions that promote the extraction of Hz vapors. At 120 F, Hz is saturated at approximately 1 psia. At lower pressures and 120 F, Hz will boil, which is an extremely efficient means to remove liquid Hz. The Hz boiling rate is predicted by equating the rate at which energy is added to the saturated liquid Hz through heaters at the tube outer wall with the energy removed from the liquid through evaporation. Boil-off fluxes were predicted by iterating through the range of local pressures with limits set by the minimum allowed pressure of 0.2 psia and maximum allowed wall temperature of 120 F established by the heaters, which gives a saturation pressure of approximately 1.0 psia. Figure 1 shows the resulting boil-off fluxes as a function of local eduction pressure. As depicted in figure 1, the flux is a strong inverse function of eduction pressure, and that minimizing the eduction pressure maximizes the boil-off flux. Also, higher outer wall temperatures lead to higher boil-off fluxes and allow for boil-off over a greater range of eduction pressures.

Pasch, James J.↗
NASA NTRS1998

Development of a Simulation Capability for the Space Station Active Rack Isolation System

To realize quality microgravity science on the International Space Station, many microgravity facilities will utilize the Active Rack Isolation System (ARIS). Simulation capabilities for ARIS will be needed to predict the microgravity environment. This paper discusses the development of a simulation model for use in predicting the performance of the ARIS in attenuating disturbances with frequency content between 0.01 Hz and 10 Hz. The derivation of the model utilizes an energy-based approach. The complete simulation includes the dynamic model of the ISPR integrated with the model for the ARIS controller so that the entire closed-loop system is simulated. Preliminary performance predictions are made for the ARIS in attenuating both off-board disturbances as well as disturbances from hardware mounted onboard the microgravity facility. These predictions suggest that the ARIS does eliminate resonant behavior detrimental to microgravity experimentation. A limited comparison is made between the simulation predictions of ARIS attenuation of off-board disturbances and results from the ARIS flight test. These comparisons show promise, but further tuning of the simulation is needed.

Johnson, Terry L.↗
NASA NTRS1990

Tank Pressure Control Experiment - A low-g mixing investigation

The Tank Pressure Control Experiment (TPCE) was conceived to meet the need for an aspect of cryogenic fluid management technology that is critical to several future national space missions: control of cryogenic storage tank pressures by active mixing. In-space testing is the only means of obtaining the fluid dynamic data necessary to develop and test predictive models of mixing. These models, when validated, will allow future cryogenic systems to be designed with more efficient and reliable pressure control systems. The objectives of the TPCE project are to characterize the fluid dynamics of jet-induced mixing in low gravity, evaluate the validity of empirical models and correlations, and provide data for use in developing and validating computational fluid dynamic models. This paper discusses prior studies of low-g mixing, the objectives and benefits of TPCE, the design and status of the payload, and preliminary results obtained from low-g aircraft testing.

Bentz, M. D.↗
NASA NTRS1990

Interesting examples of supervised continuous variable systems

The authors analyze two simple deterministic flow models for multiple buffer servers which are examples of the supervision of continuous variable systems by a discrete controller. These systems exhibit what may be regarded as the two extremes of complexity of the closed loop behavior: one is eventually periodic, the other is chaotic. The first example exhibits chaotic behavior that could be characterized statistically. The dual system, the switched server system, exhibits very predictable behavior, which is modeled by a finite state automaton. This research has application to multimodal discrete time systems where the controller can choose from a set of transition maps to implement.

Chase, Christopher↗
NASA NTRS2000

Active Rack Isolation System Program and Technical Status

The Boeing Active Rack Isolation System (ARIS) is one of the means used to isolate acceleration-sensitive scientific experiments from structurally transmitted disturbances aboard the International Space Station. The presentation provides an overview of ARIS and technical issues associated with the development of the active control system. An overview of ARIS analytical models is presented along with recent isolation performance predictions made using these models. Issues associated with commanding and capturing ARIS data are discussed and possible future options based on the ARIS ISS Characterization Experiment (ICE) Payload On-orbit Processor (POP) are outlined. An overview of the ARIS-ICE experiment scheduled to fly on ISS Flight 6A is presented. The presentation concludes with a discussion of recent- developmental work that includes passive rack damping, umbilical redesigns and advanced multivariable control design methods.

Bushnell, Glenn↗
NASA NTRS1995

Damage-mitigating control of a reusable rocket engine for high performance and extended life

The goal of damage mitigating control in reusable rocket engines is to achieve high performance with increased durability of mechanical structures such that functional lives of the critical components are increased. The major benefit is an increase in structural durability with no significant loss of performance. This report investigates the feasibility of damage mitigating control of reusable rocket engines. Phenomenological models of creep and thermo-mechanical fatigue damage have been formulated in the state-variable setting such that these models can be combined with the plant model of a reusable rocket engine, such as the Space Shuttle Main Engine (SSME), for synthesizing an optimal control policy. Specifically, a creep damage model of the main thrust chamber wall is analytically derived based on the theories of sandwich beam and viscoplasticity. This model characterizes progressive bulging-out and incremental thinning of the coolant channel ligament leading to its eventual failure by tensile rupture. The objective is to generate a closed form solution of the wall thin-out phenomenon in real time where the ligament geometry is continuously updated to account for the resulting deformation. The results are in agreement with those obtained from the finite element analyses and experimental observation for both Oxygen Free High Conductivity (OFHC) copper and a copper-zerconium-silver alloy called NARloy-Z. Due to its computational efficiency, this damage model is suitable for on-line applications of life prediction and damage mitigating control, and also permits parametric studies for off-line synthesis of damage mitigating control systems. The results are presented to demonstrate the potential of life extension of reusable rocket engines via damage mitigating control. The control system has also been simulated on a testbed to observe how the damage at different critical points can be traded off without any significant loss of engine performance. The research work reported here is built upon concepts derived from the disciplines of Controls, Thermo-fluids, Structures, and Materials. The concept of damage mitigation, as presented in this report, is not restricted to control of rocket engines. It can be applied to any system where structural durability is an important issue.

Ray, Asok↗