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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Current Methods Modeling and Simulating Icing Effects on Aircraft Performance, Stability, Control

Icing alters the shape and surface characteristics of aircraft components, which results in altered aerodynamic forces and moments caused by air flow over those iced components. The typical effects of icing are increased drag, reduced stall angle of attack, and reduced maximum lift. In addition to the performance changes, icing can also affect control surface effectiveness, hinge moments, and damping. These effects result in altered aircraft stability and control and flying qualities. Over the past 80 years, methods have been developed to understand how icing affects performance, stability, and control. Emphasis has been on wind-tunnel testing of two-dimensional subscale airfoils with various ice shapes to understand their effect on the flowfield and ultimately the aerodynamics. This research has led to wind-tunnel testing of subscale complete aircraft models to identify the integrated effects of icing on the aircraft system in terms of performance, stability, and control. Data sets of this nature enable pilot-in-the-loop simulations to be performed for pilot training or engineering evaluation of system failure impacts or control system design.

Ratvasky, Thomas P.↗
DOE OSTI2026

A data-driven approach to real-time vertical position estimation for NSTX-U vertical stability control

In this paper, a database of 77 996 plasma equilibrium reconstructions from 727 discharges during the initial operation of the NSTX-U spherical tokamak is analyzed to develop a statistically robust model of the plasma vertical position for real-time control. A variety of regression models are developed and tested, ranging in complexity from linear models to deep neural networks, and including input signals ranging from the four pairs of flux loops used historically on NSTX-U up to the full set of 389 real-time signals available to the plasma control system. A linear model based on 140 real-time magnetics signals is found to offer excellent accuracy, with a coefficient of determination R 2 = 0.906. The robustness of this model to limited training data, new operating scenarios, and signal errors is tested, and a procedure is demonstrated to tune the model parameters to optimize its robustness. A time-dependent plasma equilibrium solver, TokaMaker, is used to simulate vertical stability control in NSTX-U, demonstrating that it should be possible to iteratively tune the parameters of a linear vertical position model to stabilize both positive and negative triangularity plasmas in future experiments.

magnetic diagnostics↗
DOE OSTI2025

Safe Reinforcement Learning-Based Transient Stability Control for Islanded Microgrids With Topology Reconfiguration

This paper proposes a safe reinforcement learning (RL)-based transient stability emergency control (TSEC) method for islanded microgrids. RL requires extensive interaction with the environment to learn control strategies, hence, a data-driven approach is used as a substitute for time-consuming time-domain simulation calculations. Deep sigma point processes (DSPP), which is a Gaussian process model, is utilized to predict the normal distribution of transient stability of microgrids and to construct a transient stability chance constraint. Reward-constrained policy optimization (RCPO) can simultaneously achieve objective prediction, policy learning, and constraint cost coefficient update across multiple timescales. RCPO interacts with the DSPP-based microgrid environment through a multi-process parallel manner, greatly increasing the training speed. Case studies on a real islanded microgrid demonstrate that the proposed method can efficiently and quickly obtain the optimal emergency control strategy while adhering to all hard constraints.

14 SOLAR ENERGY↗
DOE OSTI2026

Software Control Program For Transportable Microgrid State-of-charge Balancing And Frequency Stability Controls

A deterministic state-of-charge (SOC) balancing approach software control code is introduced as an integral secondary management to primary control layer of an islanded small microgrid or nanogrid system made up of multiple grid-forming inverter/battery/solar combination systems, where each set of batteries with each inverter are on independent DC buses (i.e. non-paralleled on the DC sides). A DERMS-level control approach, algorithm and automation controller program was developed to improve coordination and enable microgrid asset compliance and SOC balancing, enabling provision of a system-level power stability support architecture, load support, and asset scalability. The architecture is configured to treat each unit or micro/nano-grid as a node in a microgrid network, allowing for autonomous DERMS control regarding load and SOC balancing and power stability. As the network grows with the addition of units, greater coordination efforts may be required. The ideal small network microgrid ranges from 2-10 inverter/battery units before additional control parameters must be considered in the existing architecture. The control approach focuses on a deterministic state-of-charge analysis as the primary level control process followed by a secondary control loop using a forced frequency-watt droop strategy to conform off-the-shelf components into behaving under a leader-follower configuration. Adopting this control scheme has been shown to allow for a balanced, unit-coordinated microgrid network, enabling stable power flow. The deterministic state-of-charge approach is introduced as an integral primary control layer of an islanded small network microgrid. A standard strategy for SOC balancing is implementing a battery management system (BMS) to control SOC on the DC side. An alternative approach is to determine how to coordinate sending and receiving power on the AC side with multiple units. The latter approach assesses all the integrated units in the microgrid network. Once the individual units are identified, further system data is required to calculate each unit's total kWh, provided information about its capability to supply or consume kWh and availability. The secondary control layer in the multi-layered small network microgrid methodology uses the primary layer’s decision to initiate frequency setpoint changes, initializing the SOC balancing. The secondary control layer considers numerous system-dependent variables to enable a charging and discharging profile based on adjustable frequency setpoints. The combined architecture will result in stable, coordinated power flow enhancing an AC microgrid's functionalities.

Myers, KurtS [Idaho National Laboratory (INL), Ida↗
NASA NTRS2007

Orion Entry Flight Control Stability and Performance

The Orion Spacecraft will be required to perform entry and landing functions for both Low Earth Orbit (LEO) and Lunar return missions, utilizing only the Command Module (CM) with its unique systems and GN&C design. This paper presents the current CM Flight Control System (FCS) design to support entry and landing, with a focus on analyses that have supported its development to date. The CM FCS will have to provide for spacecraft stability and control while following guidance or manual commands during exo-atmospheric flight, after Service Module separation, translational powered flight required of the CM, atmospheric flight supporting both direct entry and skip trajectories down to drogue chute deploy, and during roll attitude reorientation just prior to touchdown. Various studies and analyses have been performed or are on-going supporting an overall FCS design with reasonably sized Reaction Control System (RCS) jets, that minimizes fuel usage, that provides appropriate command following but with reasonable stability and control margin. Results from these efforts to date are included, with particular attention on design issues that have emerged, such as the struggle to accommodate sub-sonic pitch and yaw control without using excessively large jets that could have a detrimental impact on vehicle weight. Apollo, with a similar shape, struggled with this issue as well. Outstanding CM FCS related design and analysis issues, planned for future effort, are also briefly be discussed.

Strahan, Alan L.↗
NASA NTRS1999

Reference H Cycle 3 Stability, Control, and Flying Qualities Batch Assessments

This work is an update of the assessment completed in February of 1996, when a preliminary assessment report was issued for the Cycle 2B simulation model. The primary purpose of the final assessment was to re-evaluate each assessment against the flight control system (FCS) requirements document using the updated model. Only a limited number of final assessments were completed due to the close proximity of the release of the Langley model and the assessment deliverable date. The assessment used the nonlinear Cycle 3 simulation model because it combines nonlinear aeroelastic (quasi-static) aerodynamic with hinge moment and rate limited control surface deflections. Both Configuration Aerodynamics (Task 32) and Flight Controls (Task 36) were funded in 1996 to conduct the final stability and control assessments of the unaugmented Reference H configuration in FY96. Because the two tasks had similar output requirements, the work was divided such that Flight Controls would be responsible for the implementation and checkout of the simulation model and Configuration Aerodynamics for writing Madab "script' files, conducting the batch assessments and writing the assessment report. Additionally, Flight Controls was to investigate control surface allocations schemes different from the baseline Reference H in an effort to fulfill flying qualities criteria.

Henderson, Dennis K.↗
NASA NTRS2022

Treatment of Launch Vehicle Flight Control Stability Margin Reductions for Crewed Missions with Emphasis on Slosh Dynamics

NESC’s perspective for crewed spaceflight: Acceptance of flight control gain/phase stability margin reductions from industry standards should be accompanied by an adequately extensive technical treatment, including: •Analyzing the fundamental physics involved, with applicable simulation tool verification (particularly if results are dissimilar among rules of thumb, linear tools, nonlinear analysis, and flight data) •Conducting sensitivity studies in time and frequency domains to analyze effects of possible parameter and system variations •Studying the effects of the consequence of instability associated with offending modes by running stressing cases in time domain •Assessing alternative flight control designs to demonstrate that present design appropriately balances overall vehicle risk (i.e., quantitatively delineate chosen tradeoffs between various stability margins and vehicle performance in the context of risk/consequence) Work presented here represents an example summary of expected engineering work to flight-certify crewed missions with unstable slosh modes and reduced stability margins

Launch Vehicle Flight Control↗
DOE OSTI2018

A Riccati Solution for the Ideal MHD Plasma Response with Applications to Real-time Stability Control

To effectuate near real-time feedback control of ideal MHD instabilities in a tokamak geometry, a rapid solution for stability analysis is a prerequisite. Toward this end, we reformulate the δW stability method with a Hamilton-Jacobi theory, elucidating analytical and numerical features of the generic tokamak ideal MHD stability problem. The plasma response matrix is demonstrated to be the solution of an ideal MHD matrix Riccati differential equation (MRDE). Since Riccati equations are prevalent in the control theory literature, such a shift in perspective brings to bear a range of numerical methods that are well-suited to the robust, fast solution of control problems. We discuss the usefulness of Riccati techniques in solving the stiff ODEs often encountered in ideal MHD stability analyses-—for example, in tokamak edge and stellarator physics. We then demonstrate the applicability of such methods to an existing 2D ideal MHD stability code—DCON—enabling its parallel operation in near real-time. Output is shown to match with high accuracy, and with wall-clock time ≪ 1s. Such speed may help enable active feedback ideal MHD stability control, especially in tokamak plasmas whose ideal MHD equilibria evolve with inductive timescale τ > 1s-—as in ITER.

Parallel↗
NASA NTRS1995

A class of stabilizing controllers for flexible multibody systems

The problem of controlling a class of nonlinear multibody flexible space systems consisting of a flexible central body to which a number of articulated appendages are attached is considered. Collocated actuators and sensors are assumed, and global asymptotic stability of such systems is established under a nonlinear dissipative control law. The stability is shown to be robust to unmodeled dynamics and parametric uncertainties. For a special case in which the attitude motion of the central body is small, the system, although still nonlinear, is shown to be stabilized by linear dissipative control laws. Two types of linear controllers are considered: static dissipative (constant gain) and dynamic dissipative. The static dissipative control law is also shown to provide robust stability in the presence of certain classes of actuator and sensor nonlinearities and actuator dynamics. The results obtained for this special case can also be readily applied for controlling single-body linear flexible space structures. For this case, a synthesis technique for the design of a suboptimal dynamic dissipative controller is also presented. The results obtained in this paper are applicable to a broad class of multibody and single-body systems such as flexible multilink manipulators, multipayload space platforms, and space antennas. The stability proofs use the Lyapunov approach and exploit the inherent passivity of such systems.

Joshi, Suresh M.↗
NASA NTRS1981

A flight investigation of static stability, control augmentation, and flight director influences on helicopter IFR handling qualities

A flight experiment was conducted using the NASA-Army V/STOLAND UH-1H variable-stability helicopter to investigate the influence of several longitudinal-static-stability, control-augmentation, and flight-director parameters on helicopter flying qualities during terminal area operations in instrument conditions. This experiment, which was part of a joint NASA/FAA program pertaining to helicopter IFR airworthiness, was designed to corroborate and extend previous ground simulation results obtained in this program. Variations examined included stable and neutral longitudinal control position gradients, rate-damping and attitude-command augmentation, and raw data versus flight-director displays. Pilot rating results agreed excellently with the ground simulation data, indicating an adequate instrument capability with rate-damping augmentation and neutral statics and the need for pitch-roll attitude augmentation to achieve a satisfactory system.

Lebacqz, J. V.↗
NASA NTRS1989

Adaptive control: Stability, convergence, and robustness

The deterministic theory of adaptive control (AC) is presented in an introduction for graduate students and practicing engineers. Chapters are devoted to basic AC approaches, notation and fundamental theorems, the identification problem, model-reference AC, parameter convergence using averaging techniques, and AC robustness. Consideration is given to the use of prior information, the global stability of indirect AC schemes, multivariable AC, linearizing AC for a class of nonlinear systems, AC of linearizable minimum-phase systems, and MIMO systems decouplable by static state feedback.

Sastry, Shankar↗
NASA NTRS1950

The Longitudinal Stability, Control Effectiveness, and Control Hinge Moment Characteristics Obtained from a Flight Investigation of a Canard Missile Configuration at Transonic and Supersonic Speeds

A 60 degree delta wing canard missile configuration was flight-tested at the Langley pilotless aircraft research station at Wallops Island, Va. The results include the longitudinal stability derivatives, control effectiveness, drag characteristics, and control-surface hinge-moment characteristics for a Mach number range of 0.7 to 1.45.

Niewald, Roy J↗
NASA NTRS1956

Longitudinal and Lateral Stability, Control Characteristics, and Vertical-Tail-Load Measurements for 0.03-Scale Model of the Avro CF-105 Airplane at Mach Number 1.41

An investigation has been made in the Langley 4- by 4-foot supersonic pressure tunnel at a Mach number of 1.41 to determine the aerodynamic characteristics of an 0.03-scale model of the Avro CF-105 airplane. The investigation included the determination of the static longitudinal and lateral stability, the control and the hinge-moment characteristics of the elevator, the aileron, and the rudder, as well as the vertical-tail-load characteristics. The results indicated a minimum drag coefficient of about 0.0270, and a maximum trimmed lift-drag ratio of about 4.25 which occurs at a lift coefficient of 0.16. The directional stability decreased with increasing angle of attack until a region of static instability occurred above an angle of attack of about 9 deg.

Spearman, M. Leroy↗
NASA NTRS2022

NASA Engineering and Safety Center Technical Bulletin No. 22-05: Launch Vehicle Flight Control Stability Margin Reduction Considerations

Launch vehicle ascent stability analyses typically rely on a combination of frequency and time domain analyses. Frequency domain analysis uses a sequence of high-fidelity linear models with constant parameters spanning the ascent trajectory. Complementary time domain analysis is performed using high-fidelity, nonlinear 6-DOF simulations. Analyses are typically dispersed to verify robustness to parameter variations by showing the vehicle meets frequency domain stability margin requirements and time domain performance metrics. This Technical Bulletin outlines standard stability margin best practices and provides recommendations for treatment of deviations from industry-standard launch vehicle stability margins due to vehicle flexibility, slosh dynamics, aerodynamics, other offending dynamics, or coupling thereof.

Launch Vehicle↗