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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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At least 361 records · Page 20

Programmable control means for providing safe and controlled medication infusion

An implantable programmable infusion pump (IPIP) is disclosed and generally includes: a fluid reservoir filled with selected medication; a pump for causing a precise volumetric dosage of medication to be withdrawn from the reservoir and delivered to the appropriate site within the body; and, a control means for actuating the pump in a safe and programmable manner. The control means includes a microprocessor, a permanent memory containing a series of fixed software instructions, and a memory for storing prescription schedules, dosage limits and other data. The microprocessor actuates the pump in accordance with programmable prescription parameters and dosage limits stored in the memory. A communication link allows the control means to be remotely programmed. The control means incorporates a running integral dosage limit and other safety features which prevent an inadvertent or intentional medication overdose. The control means also monitors the pump and fluid handling system and provides an alert if any improper or potentially unsafe operation is detected.

Fischell, Robert E.↗

How Past Loss of Control Accidents May Inform Safety Cases for Advanced Control Systems on Commercial Aircraft

This paper describes five loss of control accidents involving commercial aircraft, and derives from those accidents three principles to consider when developing a potential safety case for an advanced flight control system for commercial aircraft. One, among the foundational evidence needed to support a safety case is the availability to the control system of accurate and timely information about the status and health of relevant systems and components. Two, an essential argument to be sustained in the safety case is that pilots are provided with adequate information about the control system to enable them to understand the capabilities that it provides. Three, another essential argument is that the advanced control system will not perform less safely than a good pilot.

Holloway, C. M.↗

Arbitrating Control of Control and Display Units

The ARINC 739 Switch is a computer program that arbitrates control of two multi-function control and display units (MCDUs) between (1) a commercial flight-management computer (FMC) and (2) NASA software used in research on transport aircraft. (MCDUs are the primary interfaces between pilots and FMCs on many commercial aircraft.) This program was recently redesigned into a software library that can be embedded in research application programs. As part of the redesign, this software was combined with software for creating custom pages of information to be displayed on a CDU. This software commands independent switching of the left (pilot s) and right (copilot s) MCDUs. For example, a custom CDU page can control the left CDU while the FMC controls the right CDU. The software uses menu keys to switch control of the CDU between the FMC or a custom CDU page. The software provides an interface that enables custom CDU pages to insert keystrokes into the FMC s CDU input interface. This feature allows the custom CDU pages to manipulate the FMC as if it were a pilot.

Sugden, Paul C.↗

Development and Operation of an Automatic Rotor Trim Control System for use During the UH-60 Individual Blade Control Wind Tunnel Test

A full-scale wind tunnel test to evaluate the effects of Individual Blade Control (IBC) on the performance, vibration, noise and loads of a UH-60A rotor was recently completed in the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel [1]. A key component of this wind tunnel test was an automatic rotor trim control system that allowed the rotor trim state to be set more precisely, quickly and repeatably than was possible with the rotor operator setting the trim condition manually. The trim control system was also able to maintain the desired trim condition through changes in IBC actuation both in open- and closed-loop IBC modes, and through long-period transients in wind tunnel flow. This ability of the trim control system to automatically set and maintain a steady rotor trim enabled the effects of different IBC inputs to be compared at common trim conditions and to perform these tests quickly without requiring the rotor operator to re-trim the rotor. The trim control system described in this paper was developed specifically for use during the IBC wind tunnel test

Theodore, Colin R.↗

Computer Controlled Solid State Lighting Assembly to Emulate Diurnal Cycle and Improve Circadian Rhythm Control

A light system can simultaneously emulate more than one different diurnal cycle to individually improve circadian rhythm control for more than one observer by having each light fixture autonomously self-controlled. Each light fixture is mountable in respective locations to individually treat respective observers. Each light fixture includes one or more light elements mounted to a housing and are controllable to emit a selected light intensity at a selected light temperature. A micro controller is contained in the housing and includes memory containing instructions for one or more automatic diurnal cycle protocols. The micro controller is in communication with the memory and the one or more light elements to execute the instructions to configure the light fixture to vary the light intensity and the light temperature of the emitted light.

Holbert, Eirik↗

Pterodactyl: Guidance and Control of a Symmetric Deployable Entry Vehicle using an Aerodynamic Control System

The NASA-funded Pterodactyl project seeks to advance the current state-of-the-art for entry vehicles by developing novel guidance and control technologies for Deployable Entry Vehicles (DEVs). This paper presents the guidance and control design and analysis for a mechanically-deployed DEV with a symmetric aeroshell and aerodynamic control surfaces. We present guidance tuning using both bank angle modulation with the Fully-Numerical Predictor Corrector Entry Guidance technique (FNPEG) and angle of attack and sideslip modulation with FNPEG with uncoupled range control (FNPEG URC). We show the control system design and simulation results for tracking both types of guidance commands.

Benjamin W L Margolis↗

Pterodactyl: Guidance and Control of a Symmetric Deployable Entry Vehicle using an Aerodynamic Control System

The NASA-funded Pterodactyl project seeks to advance the current state-of-the-art for entry vehicles by developing novel guidance and control technologies for Deployable Entry Vehicles (DEVs). This paper presents the guidance and control design and analysis for a mechanically-deployed DEV with a symmetric aeroshell and aerodynamic control surfaces. We present guidance tuning using both bank angle modulation with the Fully-Numerical Predictor Corrector Entry Guidance technique (FNPEG) and angle of attack and sideslip modulation with FNPEG with uncoupled range control (FNPEG URC). We show the control system design and simulation results for tracking both types of guidance commands.

Benjamin Margolis↗

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. Here, in order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

42 ENGINEERING↗

Autonomous Inverter Controls for Resilient and Secure Grid Operation: Vector Control Design for Grid Forming

The project addresses both fundamental and practical challenges of GFM/GFL inverter control for the power grids with high inverter based resources (IBRs) penetration. A data- driven modeling technique is applied to accurately model dynamics of PWM inverters, including electromagnetic-transient (EMT). Systematic and integrative designs of grid- forming (GFM) and grid-following (GFL) primary controls are developed to guarantee system performance under either normal or abnormal operating conditions without violating constraints. This modeling and control framework provides black-start capability in case of an outage without relying on rotating generators, and its secondary control is also shown to enhance resilience against cyber-physical attacks.

14 SOLAR ENERGY↗

Minimizing Electric Lighting Use With LASSI Lighting Controls in Controlled Environment Agriculture

The majority of energy use in controlled environment agriculture is typically from electric lighting. Certain lighting controls can help minimize the energy required in these operations. This analysis simulates a greenhouse with different types of lighting controls in different U.S. climates to explore the effects of the lighting controls on energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Autonomous control for Heat-Pipe microreactor using Data-Driven model predictive control

To enable a self-regulating capability for heat pipe (HP) microreactors, an anticipatory control strategy achieved via model predictive control (MPC) could proactively respond to potential disturbances and deviations in operating setpoints. This paper demonstrates data-driven methods for predicting the distribution and transient of temperatures and heat fluxes at selected components and regions in a 37-HP system, based on which the optimal control actions in response to changes in user-defined setpoints can be found. We present the development and validation of linear state-space model, feedfoward, and recurrent neural networks. Here, we compare the performance of MPCs with different modeling approaches in terms of following setpoints for temperatures and averaged output heat fluxes. The accuracies of the three data-driven models are similar, but the control actions initiated by neural-network-based MPC can better adapt to drastic changes in setpoints yet generate the smallest errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Learning-based CO 2 concentration prediction: Application to indoor air quality control using demand-controlled ventilation

There have been increasing concerns over the air quality inside buildings as high levels of bio-effluents can cause nausea, dizziness, headaches, and fatigue to the people working in those spaces. First published in 2004 as Standard 62.1, ASHRAE Standard 62.2-2019 requires highly occupied spaces to implement heating, ventilation, and air conditioning (HVAC) that can dilute contaminants produced by occupants. In this regard, occupant-centric ventilation control has been regarded as an effective practice to maintain a satisfactory indoor air quality (IAQ) when dealing with highly variable occupancy environments. However, few established models in current literature and practice consider dynamic occupancy behavior and adaptive IAQ control. To address this gap, a dynamic indoor CO2 model is constructed using machine learning algorithms to forecast CO2concentrations across a range of forecasting horizons. Herein, we tuned and compared six state-of-the-algorithms—including Support Vector Machine, Ada Boost, Random Forest, Gradient Boosting, Logistic Regression, and Multilayer Perceptron. The algorithms’ performances are validated using CO 2 and historical meteorological data collected from a campus classroom with a variable occupancy rate. Simulation results showed that Multilayer Perceptron can strongly predict the volatile CO 2 behavior and also outperforms other algorithms in terms of accuracy. Furthermore, a control strategy capable of modeling and detecting dynamic patterns of CO 2 level is utilized to modulate the ventilation rate in real-time and also reduce the energy consumption. The proposed controller reduced the HVAC fan’s energy consumption by 51.4% and provide ventilation as needed per the ASHRAE standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nonlinear behavior in high-frequency aggregate control of thermostatically controlled loads

Coordinated control of electric loads can provide valuable grid services, such as frequency regulation. However, due to the nonlinear characteristics of such load ensembles, it is important to systematically analyze their behavior and establish a thorough understanding of undesirable phenomena that can potentially arise. In this paper, we analyze the frequency response of an aggregate control scheme, with the goal of exploring controller performance limits. We show that rapid switching commands can induce oscillations in the power output due to the inherent lockout mechanism of the underlying devices. Here, we demonstrate that highly detailed aggregate models are required to capture such phenomena. Such models enable deeper understanding of the control boundaries and therefore play an important role in avoiding the introduction of undesirable effects on the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development and assessment of a model predictive controller enabling anticipatory control strategies for a heat-pipe system

To support the reliable and resilient operation of modular reactors and microreactors, anticipatory control strategies have been proposed for achieving faster-than-real-time predictions and decision-making capabilities in anticipation of potential anomalies, including setpoint changes and cyber incidents. Here this work presents how anticipatory control strategies can be implemented via model predictive control (MPC) of a single heat pipe’s temperature. Considering the uncertainty in developing and applying MPC, this work evaluates MPC performance given three different model forms: a linear response surface model, an artificial neural network (ANN), and an autoregressive model with exogenous input (ARX). This work also evaluates the impacts of different input biases and variance on MPC performance in order to account for potential sensor reading variations due to cyber incidents. We observe that nonparametric models such as the ANN and ARX result in more fluctuated control actions compared to the MPC applied to the linear response surface model. However, when the cyber incidents are of a large magnitude, the linear response surface model produces smaller feasible regions than the nonparametric models under identical constraints.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Enhancing strontium clock atom interferometry using quantum optimal control

Strontium clock atom interferometry is a promising new technology, with multiple experiments under development around the world to explore its potential for dark matter and gravitational wave detection. In these detectors, large momentum transfer using sequences of many laser pulses is necessary, and thus high-fidelity pulses are important since small errors become magnified. Quantum optimal control (QOC) is a framework for developing control pulse waveforms that achieve high fidelity and are robust against experimental imperfections. Resonant single-photon transitions using the narrow clock transition of strontium involve significantly different quantum dynamics than more established atom interferometry methods based on far-detuned two-photon Raman or Bragg transitions, which leads to new opportunities and challenges when applying QOC. Here, we study in simulation QOC pulses for strontium clock interferometry and demonstrate their advantage over basic square pulses (primitive pulses) and composite pulses in terms of robustness against multiple noise channels. In conclusion, this could improve the scale of large momentum transfer in Sr clock interferometers, paving the way to achieving these scientific goals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Reinforcement-Learning-Based Smart Water Heater Control: An Actual Deployment

Utilizing smart control algorithms for electric water heaters (EWHs) is essential for fully harnessing the demand response (DR) potential of EWHs. For this reason, the use of reinforcement learning (RL) algorithms for EWHs has received increasing attention in recent years. However, existing RL approaches are either simulation-based or use pretrained RL agents. To this end, this paper presents the real-world deployment of a set of model-free RL approaches that aim to minimize the electricity cost of a EWH under a time-of-use electricity pricing policy using standard DR commands (e.g., shed, load up). The experiment results showed that the RL agents can help save electricity cost in the range of 11% to 14% compared to the baseline operation. This study demonstrated that RL-based EWH controllers can be deployed in real world without any prior training and can still save electricity cost.

deep learning↗

Irradiance and spectral distribution control system for controlled environment chambers

This paper describes a closed-loop control system for controlling the irradiance and spectral quality generated by fluorescent lamps in a controlled environment chamber. The 400 to 800 nm irradiance and the ratio of the red waveband (600 to 700 nm) to the far-red waveband (700 to 800 nm) were independently controlled and varied as functions of time. A suggested application is to investigate the possibility of synergistic effects of changing irradiance levels and changing spectral distributions on photoperiodism and photomorphogenesis.

NASA Center KSC↗