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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Real-time Adaptive Control Using Neural Generalized Predictive Control

The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

Haley, Pam↗
NASA NTRS2004

Adaptive model-based control systems and methods for controlling a gas turbine

Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).

Brunell, Brent Jerome↗
NASA NTRS2004

Heat Control via Torque Control in Friction Stir Welding

In a proposed advance in friction stir welding, the torque exerted on the workpiece by the friction stir pin would be measured and controlled in an effort to measure and control the total heat input to the workpiece. The total heat input to the workpiece is an important parameter of any welding process (fusion or friction stir welding). In fusion welding, measurement and control of heat input is a difficult problem. However, in friction stir welding, the basic principle of operation affords the potential of a straightforward solution: Neglecting thermal losses through the pin and the spindle that supports it, the rate of heat input to the workpiece is the product of the torque and the speed of rotation of the friction stir weld pin and, hence, of the spindle. Therefore, if one acquires and suitably processes data on torque and rotation and controls the torque, the rotation, or both, one should be able to control the heat input into the workpiece. In conventional practice in friction stir welding, one uses feedback control of the spindle motor to maintain a constant speed of rotation. According to the proposal, one would not maintain a constant speed of rotation: Instead, one would use feedback control to maintain a constant torque and would measure the speed of rotation while allowing it to vary. The torque exerted on the workpiece would be estimated as the product of (1) the torque-multiplication ratio of the spindle belt and/or gear drive, (2) the force measured by a load cell mechanically coupled to the spindle motor, and (3) the moment arm of the load cell. Hence, the output of the load cell would be used as a feedback signal for controlling the torque (see figure).

Venable, Richard↗
NASA NTRS2012

Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks

Recent developments in fly-by-wire control architectures for rotorcraft have introduced new interest in the identification of time-varying pilot control behavior in multi-axis control tasks. In this paper a maximum likelihood estimation method is used to estimate the parameters of a pilot model with time-dependent sigmoid functions to characterize time-varying human control behavior. An experiment was performed by 9 general aviation pilots who had to perform a simultaneous roll and pitch control task with time-varying aircraft dynamics. In 8 different conditions, the axis containing the time-varying dynamics and the growth factor of the dynamics were varied, allowing for an analysis of the performance of the estimation method when estimating time-dependent parameter functions. In addition, a detailed analysis of pilots adaptation to the time-varying aircraft dynamics in both the roll and pitch axes could be performed. Pilot control behavior in both axes was significantly affected by the time-varying aircraft dynamics in roll and pitch, and by the growth factor. The main effect was found in the axis that contained the time-varying dynamics. However, pilot control behavior also changed over time in the axis not containing the time-varying aircraft dynamics. This indicates that some cross coupling exists in the perception and control processes between the roll and pitch axes.

Zaal, Peter M. T.↗
NASA NTRS2013

Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting

Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.

Trujillo, Anna↗
NASA NTRS2017

Flex Dynamics Avoidance Control of the NEA Scout Solar Sail Spacecraft's Reaction Control System

The Attitude Control System (ACS) is developed for a Near Earth Asteroid (NEA) Scout mission using a solar sail. The NEA-Scout spacecraft is a 6U cubesat with an 86 square-meter solar sail. NEA Scout will launch on Space Launch System (SLS) Exploration Mission 1 (EM-1), currently scheduled to launch in 2018. The spacecraft will rendezvous with a target asteroid after a two year journey, and will conduct science imagery. The solar sail spacecraft ACS consists of three major actuating subsystems: a Reaction Wheel (RW) control system, a Reaction Control System (RCS), and an Adjustable Mass Translator (AMT) system. The three subsystems allow for a wide range of spacecraft attitude control capabilities, needed for the different phases of the NEA-Scout mission. Because the sail is a flexible structure, care must be taken in designing a control system to avoid exciting the structural modes of the sail. This is especially true for the RCS, which uses pulse actuated, cold-gas jets to control the spacecraft's attitude. While the reaction wheels can be commanded smoothly, the RCS jets are simple on-off actuators. Long duration firing of the RCS jets - firings greater than one second - can be thought of as step inputs to the spacecraft's torque. On the other hand, short duration firings - pulses on the order of 0.1 seconds - can be thought of as impulses in the spacecraft's torque. These types of inputs will excite the structural modes of the spacecraft, causing the sail to oscillate. Sail oscillations are undesirable for many reasons. Mainly, these oscillations will feed into the spacecraft attitude sensors and pointing accuracy, and long term oscillations may be undesirable over the lifetime of the solar sail. In order to limit the sail oscillations, an RCS control scheme is being developed to minimize sail excitations. Specifically, an input shaping scheme similar to the method described in Reference 1 will be employed. A detailed description of the RCS control scheme will be provided with particular emphasis on flexible body excitation. The RCS performance will be provided to show that sail and boom excitation is minimized.

Heaton Andrew↗
DOE OSTI2023

Virtual supervisory control and data acquisition (SCADA) automation controller

One or more virtual supervisory control and data acquisition (SCADA) controllers are provided. The virtual SCADA controller(s) may be deployed upon a detection of a failure of a physical SCADA controller. An on-site module may detect failure including a security breach which causes the physical SCADA controller to be disconnected from a network and the virtual SCADA controller(s) to take over control. The virtual SCADA controller(s) may be on-site or off-site.

Smith, Jared M.↗
DOE OSTI2012

Microwave Ablation of Porcine Kidneys in vivo: Effect of two Different Ablation Modes ('Temperature Control' and 'Power Control') on Procedural Outcome

Purpose: This study was designed to analyze the effect of two different ablation modes ('temperature control' and 'power control') of a microwave system on procedural outcome in porcine kidneys in vivo. Methods: A commercially available microwave system (Avecure Microwave Generator; MedWaves, San Diego, CA) was used. The system offers the possibility to ablate with two different ablation modes: temperature control and power control. Thirty-two microwave ablations were performed in 16 kidneys of 8 pigs. In each animal, one kidney was ablated twice by applying temperature control (ablation duration set point at 60 s, ablation temperature set point at 96 Degree-Sign C, automatic power set point; group I). The other kidney was ablated twice by applying power control (ablation duration set point at 60 s, ablation temperature set point at 96 Degree-Sign C, ablation power set point at 24 W; group II). Procedural outcome was analyzed: (1) technical success (e.g., system failures, duration of the ablation cycle), and (2) ablation geometry (e.g., long axis diameter, short axis diameter, and circularity). Results: System failures occurred in 0% in group I and 13% in group II. Duration of the ablation cycle was 60 {+-} 0 s in group I and 102 {+-} 21 s in group II. Long axis diameter was 20.3 {+-} 4.6 mm in group I and 19.8 {+-} 3.5 mm in group II (not significant (NS)). Short axis diameter was 10.3 {+-} 2 mm in group I and 10.5 {+-} 2.4 mm in group II (NS). Circularity was 0.5 {+-} 0.1 in group I and 0.5 {+-} 0.1 in group II (NS). Conclusions: Microwave ablations performed with temperature control showed fewer system failures and were finished faster. Both ablation modes demonstrated no significant differences with respect to ablation geometry.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Reduced Switching Frequency Finite Control Set Model Predictive Control (FCS-MPC) for DFIG

An enhanced Finite Control Set Model Predictive Control (FCS-MPC) strategy with a two-step prediction horizon for a Doubly-Fed Induction Generator (DFIG) is the focus of this paper. The DFIG and RL filter's discrete-time model is used in the proposed control scheme for a two-step prediction horizon of rotor and filter currents for the converter's eight possible switching states. Afterward, the control algorithm selects the ideal switching state, which minimizes currents' objective function. The proposed control scheme does not require a modulation stage for internal controllers. We use Lagrange extrapolations to predict the dynamic changes in currents. The switching frequency reduction is achieved by integrating an optimization constraint in the algorithm's cost function. Furthermore, the Total Harmonic Distortion level of currents is kept below 5%, according to IEEE Std 519-14. Obtained results reveal that the switching frequency of the DFIG converters is considerably reduced without losing control; it is reduced by 13.89KHz for the Grid Side Converter (GSC) and by 1.78KHz for the Rotor Side Converter (RSC).

doubly-fed induction generator↗
DOE OSTI2021

Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion

In this simulation study, cycle-to-cycle fuel control was used to reduce CCV by injecting additional fuel in operating conditions with sporadic misfires and partial burns. An optimal control policy was proposed that utilizes 1) a physics-based model that tracks in-cylinder gas composition and 2) a one-step-ahead prediction of the combustion efficiency based on a kernel density estimator. The optimal solution, however, presents a tradeoff between the reduction in combustion CCV and the increase in fuel injection quantity required to stabilize the charge. Such a tradeoff can be ad- just by a single parameter embedded in the cost function.

Maldonado, BryanP. [Oak Ridge National Lab. (ORNL)↗
DOE OSTI2017

A Tutorial on Control-Oriented Modeling and Control of Wind Farms

Wind turbines are often sited together in wind farms as it is economically advantageous. However, the wake inevitably created by every turbine will lead to a time-varying interaction between the individual turbines. Common practice in industry has been to control turbines individually and ignore this interaction while optimizing the power and loads of the individual turbines. However, turbines that are in a wake experience reduced wind speed and increased turbulence, leading to a reduced energy extraction and increased dynamic mechanical loads on the turbine, respectively. Neglecting the dynamic interaction between turbines in control will therefore lead to suboptimal behaviour of the total wind farm. Therefore, wind farm control has been receiving an increasing amount of attention over the past years, with the focus on increasing the total power production and reducing the dynamic loading on the turbines. In this paper, wind farm control-oriented modeling and control concepts are explained. In addition, recent developments and literature are discussed and categorized. This paper can serve as a source of background information and provides many references regarding control-oriented modeling and control of wind farms.

17 WIND ENERGY↗
DOE OSTI2021

A Comparative Study of Model Predictive Control and Optimal Causal Control for Heaving Point Absorbers

Efforts by various researchers in recent years to design simple causal control laws that can be applied to WEC devices suggest that these controllers can yield similar levels of energy output as those of more complex non-causal controllers. However, most studies were established without adequately considering device and power conversion system constraints which are relevant design drivers from a cost and economic point of view. It is therefore imperative to understand the benefits of MPC compared to causal control from a performance and constraint handling perspective. In this paper, we compare linear MPC to a casual controller that incorporates constraint handling to benchmark its performance on a one DoF heaving point absorber in a range of wave conditions. Our analysis demonstrates that MPC provides significant performance advantages compared to an optimized causal controller, particularly if significant constraints on device motion and/or forces are imposed. We further demonstrate that distinct control performance regions can be established that correlate well with classical point absorber and volumetric limits of the wave energy conversion device.

42 ENGINEERING↗
DOE OSTI2024

Towards intelligent emergency control for large-scale power systems: Convergence of learning, physics, computing and control

Here, this paper has delved into the pressing need for intelligent emergency control in large-scale power systems, which are experiencing significant transformations and are operating closer to their limits with more uncertainties. Learning-based control methods are promising and have shown effectiveness for intelligent power system control. However, when they are applied to large-scale power systems, there are multifaceted challenges such as scalability, adaptiveness, and security posed by the complex power system landscape, which demand comprehensive solutions. The paper first proposes and instantiates a convergence framework for integrating power systems physics, machine learning, advanced computing, and grid control to realize intelligent grid control at a large scale. Our developed methods and platform based on the convergence framework have been applied to a large (more than 3000 buses) Texas power system, and tested with 56 000 scenarios. Our work achieved a 26% reduction in load shedding on average and outperformed existing rule-based control in 99.7% of the test scenarios. The results demonstrated the potential of the proposed convergence framework and DRL-based intelligent control for the future grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Synthesis of mixed-valent [alpha]- and [beta]-NaFe[subscript 2]O[subscript 3] polymorphs under controlled partial oxygen pressure

Synthesis of mixed valent compounds, especially when multiple polymorphs exist, requires careful control of the preparation conditions. {alpha}- and {beta}-NaFe{sub 2}O{sub 3} polymorphs were synthesized under controlled partial oxygen pressure (pO{sub 2}). pO{sub 2} regions of stability at 850 C were determined for both phases for the first time. A modified oxygen buffer method was developed for the facile preparation of mixed valent oxides under controlled pO{sub 2}. {beta}-NaFe{sub 2}O{sub 3} is the only known n = 2 member of the AM{sub n}O{sub n+1} (A = alkali metal, M = 3d metal) rock-salt related homolog series with layered cation ordering. The possibility of new members of the homolog series with other 3d metals is considered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Nowcasting, predictive control, and feedback control for temperature regulation in a novel hybrid solar-electric reactor for continuous solar-thermal chemical processing

A novel 15 kW reactor for the hybridization of concentrated solar and conventional electric heat was fabricated for renewable and continuous chemical processing at temperatures up to 1700 °C. Solar-electric controllers based on feedback or predictive linear models were used to regulate the device at 925 °C for the production of syngas via the gasification of carbon. The system was challenged with cloud transients programmed on a 45 kW high-flux solar simulator that approximated weather observed in the San Luis Valley (Colorado, USA). In experiment it was found that model predictive control with a 1 min ahead nowcast of incipient clouding best regulated solar-electric reactor temperatures, potentially averting thermal fatigue. Upon clouding, model predictive control with a nowcast yielded temperature disturbances of ±10 °C, whereas feedback control alone featured ±25 °C excursions. Overall, the performance of model predictive control with a nowcast was 75% better than feedback as indicated by the integral squared error of temperature excursion residuals. The importance of nowcast accuracy was explored, and although the model-based controller was robust to forecast amplitude inaccuracy, temporal forecast inaccuracy wholly negated the benefits of predictive control.

14 SOLAR ENERGY↗
DOE OSTI2019

Diesel Generator Controller Evaluation via Controller-Hardware-in-the-Loop for Various Microgrid Operation Modes

This paper presents the Controller-Hardware-in-the-Loop (CHIL) evaluation of a diesel generator controller for various microgrid operation modes. The model of the diesel generator (governor, exciter, and primary control) is simulated in real time, and the secondary control is implemented in a real hardware controller, Woodward easYgen, which is tested via CHIL with different microgrid configurations under microgrid transition operations. The experimental results demonstrate that the control settings and configuration of the Woodward controller work correctly for different microgrids under microgrid transition operations, which provides confidence for site commissioning.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Performance Evaluation of Data-Enhanced Hierarchical Control for Grid Operations

This paper presents a hardware-in-the-loop (HIL) simulation to evaluate the performance of voltage regulation of Data-Enhanced Hierarchical Control (DEHC). This DEHC uses an advanced distribution management system (ADMS) for grid operations to control legacy and grid-edge devices and coordinate with distributed energy management systems (DERMS) to manage high penetrations of photovoltaics (PV) on a utility distribution system. The HIL platform provides realistic laboratory testing, including accurate modeling (legacy devices, grid-edge devices, and PV) of the real-world distribution system from a utility partner, a real controller (ADMS), software controller DERMS, hardware grid-edge devices, and standard communications protocols. The test results demonstrate functionalities of the integrated platform and the performance of voltage regulation of the coordinated control systems. Based on laboratory testing, the utility can set up the same grid-automation system to manage DERs, legacy devices, and grid-edge devices to achieve their system-level control and operation objectives (e.g., voltage regulation), thus de-risking potential issues such as instability for field deployment.

41 EE - Solar Energy Technologies Office (EE-4S)↗