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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

System For Research On Multiple-Arm Robots

Kali system of computer programs and equipment provides environment for research on distributed programming and distributed control of coordinated-multiple-arm robots. Suitable for telerobotics research involving sensing and execution of low level tasks. Software and configuration of hardware designed flexible so system modified easily to test various concepts in control and programming of robots, including multiple-arm control, redundant-arm control, shared control, traded control, force control, force/position hybrid control, design and integration of sensors, teleoperation, task-space description and control, methods of adaptive control, control of flexible arms, and human factors.

Backes, Paul G.↗
NASA NTRS1991

Optimizing aircraft performance with adaptive, integrated flight/propulsion control

The Performance-Seeking Control (PSC) integrated flight/propulsion adaptive control algorithm presented was developed in order to optimize total aircraft performance during steady-state engine operation. The PSC multimode algorithm minimizes fuel consumption at cruise conditions, while maximizing excess thrust during aircraft accelerations, climbs, and dashes, and simultaneously extending engine service life through reduction of fan-driving turbine inlet temperature upon engagement of the extended-life mode. The engine models incorporated by the PSC are continually upgraded, using a Kalman filter to detect anomalous operations. The PSC algorithm will be flight-demonstrated by an F-15 at NASA-Dryden.

Smith, R. H.↗
NASA NTRS1990

NASA-UCLA Workshop on Computational Techniques in Identification and Control of Flexible Flight Structures, Lake Arrowhead, CA, Nov. 2-4, 1989, Proceedings

The present conference on the identification and control of flexible flight structures with computational techniques encompasses existing and planned testbeds, modeling techniques, adaptive control, and numerical computation and simulation. Specific issues addressed include the NASA/MFSC ground test facility, an active control test on the NASA Minimast, the Astrex testbed for large precision space structures, the dynamic analysis of truss-beam modeling, combined structure-controls-integrated optimization, distributed parameter modeling applicable to the control of flexible flight structures, and approaches to nonclassically damped dynamic systems. Also addressed are adaptive control concepts, techniques for vibration and decentralized slew maneuver control, the discretization of second-order-in-time differential equations which are applicable to nonlinear wave problems, the finite-dimensional approximations of Riccati equations, and numerical simulations of actively controlled space structures.

Balakrishnan, A. V.↗
NASA NTRS1993

Active Suppression Of Vibrations On Elastic Beams

Pairs of colocated piezoelectric transducers, independently controlled by multichannel adaptive controller, employed as actuators and sensors to achieve simultaneous attenuation of both extensional and flexural motion. Single pair used to provide simultaneous control of flexural and extensional waves, or two pairs used to control torsional motion also. Capability due to nature of piezoelectric transducers, when bonded to surfaces of structures and activated by oscillating voltages, generate corresponding oscillating distributions of stresses in structures. Phases and amplitudes of actuator voltages adjusted by controller to impede flow of vibrational energy simultaneously, in waves of various forms, beyond locations of actuators. Concept applies equally to harmonic or random response of structure and to multiple responses of structure to transverse bending, torsion, and compression within structural element. System has potential for many situations in which predominant vibration transmission path through framelike structure.

Silcox, Richard J.↗
NASA NTRS2005

Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

Burken, John J.↗
NASA NTRS2008

2007 Research and Engineering Annual Report

Selected research and technology activities at NASA Dryden Flight Research Center are summarized. These following activities exemplify the Center's varied and productive research efforts: Developing a Requirements Development Guide for an Automatic Ground Collision Avoidance System; Digital Terrain Data Compression and Rendering for Automatic Ground Collision Avoidance Systems; Nonlinear Flutter/Limit Cycle Oscillations Prediction Tool; Nonlinear System Identification Using Orthonormal Bases: Application to Aeroelastic/Aeroservoelastic Systems; Critical Aerodynamic Flow Feature Indicators: Towards Application with the Aerostructures Test Wing; Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm; Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool; Extension of Ko Straight-Beam Displacement Theory to the Deformed Shape Predictions of Curved Structures; F-15B with Phoenix Missile and Pylon Assembly--Drag Force Estimation; Mass Property Testing of Phoenix Missile Hypersonic Testbed Hardware; ARMD Hypersonics Project Materials and Structures: Testing of Scramjet Thermal Protection System Concepts; High-Temperature Modal Survey of the Ruddervator Subcomponent Test Article; ARMD Hypersonics Project Materials and Structures: C/SiC Ruddervator Subcomponent Test and Analysis Task; Ground Vibration Testing and Model Correlation of the Phoenix Missile Hypersonic Testbed; Phoenix Missile Hypersonic Testbed: Performance Design and Analysis; Crew Exploration Vehicle Launch Abort System-Pad Abort-1 (PA-1) Flight Test; Testing the Orion (Crew Exploration Vehicle) Launch Abort System-Ascent Abort-1 (AA-1) Flight Test; SOFIA Flight-Test Flutter Prediction Methodology; SOFIA Closed-Door Aerodynamic Analyses; SOFIA Handling Qualities Evaluation for Closed-Door Operations; C-17 Support of IRAC Engine Model Development; Current Capabilities and Future Upgrade Plans of the C-17 Data Rack; Intelligent Data Mining Capabilities as Applied to Integrated Vehicle Health Management; STARS Flight Demonstration No. 2 IP Data Formatter; Space-Based Telemetry and Range Safety (STARS) Flight Demonstration No. 2 Range User Flight Test Results; Aerodynamic Effects of the Quiet Spike(tm) on an F-15B Aircraft; F-15 Intelligent Flight Controls-Increased Destabilization Failure; F-15 Integrated Resilient Aircraft Control (IRAC) Improved Adaptive Controller; Aeroelastic Analysis of the Ikhana/Fire Pod System; Ikhana: Western States Fire Missions Utilizing the Ames Research Center Fire Sensor; Ikhana: Fiber-Optic Wing Shape Sensors; Ikhana: ARTS III; SOFIA Closed-Door Flutter Envelope Flight Testing; F-15B Quiet Spike(TM) Aeroservoelastic Flight Test Data Analysis; and UAVSAR Platform Precision Autopilot Flight Results.

Stoliker, Patrick↗
NASA NTRSDate not supplied

TPSAS-NF1676L-15456-DND

Concept that combines the advances in - flight control with L1 adaptive control coverage of the flight envelope with a single design and - parameter identification (PID) with an automated, efficient and accurate method for global aerodynamic modeling to enable rapid transition to flight with minimal initial knowledge of the vehicle dynamics.

Carey Buttrill↗
NASA NTRS2008

An Adaptive Instability Suppression Controls Method for Aircraft Gas Turbine Engine Combustors

An adaptive controls method for instability suppression in gas turbine engine combustors has been developed and successfully tested with a realistic aircraft engine combustor rig. This testing was part of a program that demonstrated, for the first time, successful active combustor instability control in an aircraft gas turbine engine-like environment. The controls method is called Adaptive Sliding Phasor Averaged Control. Testing of the control method has been conducted in an experimental rig with different configurations designed to simulate combustors with instabilities of about 530 and 315 Hz. Results demonstrate the effectiveness of this method in suppressing combustor instabilities. In addition, a dramatic improvement in suppression of the instability was achieved by focusing control on the second harmonic of the instability. This is believed to be due to a phenomena discovered and reported earlier, the so called Intra-Harmonic Coupling. These results may have implications for future research in combustor instability control.

Kopasakis, George↗
NASA NTRS2002

Adaptive Instability Suppression Controls in a Liquid-fueled Combustor

An adaptive control algorithm has been developed for the suppression of combustion thermo-acoustic instabilities. This technique involves modulating the fuel flow in the combustor with a control phase that continuously slides within the stable phase region, in a back and forth motion. The control method is referred to as Adaptive Sliding Phasor Averaged Control (ASPAC). The control method is evaluated against a simplified simulation of the combustion instability. Plans are to validate the control approach against a more physics-based model and an actual experimental combustor rig.

Kopasakis, George↗
DOE OSTI2022

Traffic Signal Control With Adaptive Online-Learning Scheme Using Multiple-Model Neural Networks

This article proposes a new traffic signal control algorithm to deal with unknown-traffic-system uncertainties and reduce delays in vehicle travel time. Unknown-traffic-system dynamics are approximated using a recurrent neural network (NN). To accurately identify the traffic system model, an online-learning scheme is developed to switch among a set of candidate NNs (i.e., multiple-model NNs) based on their estimation errors. Then, a bank of optimal signal-timing controllers is designed based on the online identification of the traffic system. Simulation studies have been carried out for the obtained control strategies using multiple-model NNs, and the desired results have been obtained. Moreover, compared with the widely used actuated traffic signal control schemes, it is shown that the proposed method can reduce vehicle travel delays and improve traffic system robustness.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1990

Position control of redundant manipulators using an adaptive error-based control scheme

A Cartesian-space control scheme is developed to control the motion of kinematically redundant manipulators with 7 degrees of freedom (DOF). The control scheme consists mainly of proportional derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories. The adaptation law is derived using the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that the manipulator performs non-compliant and slowly-varying motions. The developed control scheme is computationally efficient because its implementation does not require the computation of the manipulator dynamics. Computer simulation performed to evaluate the control scheme performance is presented and discussed.

Nguyen, Charles C.↗
NASA NTRS1973

Digital adaptive model following control

Development of an implementable digital adaptive control system requires a control law that can be efficiently adjusted during system operation and an identification algorithm that is capable of supplying parameter estimates at an accuracy and rate specified by the controller characteristics. To this effect a control law has been derived based upon the minimization of a weighted combination of the instantaneous squared error between the states of a linear plant and model at the next stage and the present control energy. The result is a control signal that is a linear combination of plant states, model states, and any model inputs. Explicit formula are available for computing the pertinent gains. To illustrate the utility of such a control law, its application to typical linearized lateral aircraft dynamics is currently being considered.

Alag, G.↗
NASA NTRS2000

Bioelectric Control of a 757 Class High Fidelity Aircraft Simulation

This paper presents results of a recent experiment in fine grain Electromyographic (EMG) signal recognition, We demonstrate bioelectric flight control of 757 class simulation aircraft landing at San Francisco International Airport. The physical instrumentality of a pilot control stick is not used. A pilot closes a fist in empty air and performs control movements which are captured by a dry electrode array on the arm, analyzed and routed through a flight director permitting full pilot outer loop control of the simulation. A Vision Dome immersive display is used to create a VR world for the aircraft body mechanics and flight changes to pilot movements. Inner loop surfaces and differential aircraft thrust is controlled using a hybrid neural network architecture that combines a damage adaptive controller (Jorgensen 1998, Totah 1998) with a propulsion only based control system (Bull & Kaneshige 1997). Thus the 757 aircraft is not only being flown bioelectrically at the pilot level but also demonstrates damage adaptive neural network control permitting adaptation to severe changes in the physical flight characteristics of the aircraft at the inner loop level. To compensate for accident scenarios, the aircraft uses remaining control surface authority and differential thrust from the engines. To the best of our knowledge this is the first time real time bioelectric fine-grained control, differential thrust based control, and neural network damage adaptive control have been integrated into a single flight demonstration. The paper describes the EMG pattern recognition system and the bioelectric pattern recognition methodology.

Jorgensen, Charles↗
NASA NTRS1993

Operator versus computer control of adaptive automation

Adaptive automation refers to real-time allocation of functions between the human operator and automated subsystems. The article reports the results of a series of experiments whose aim is to examine the effects of adaptive automation on operator performance during multi-task flight simulation, and to provide an empirical basis for evaluations of different forms of adaptive logic. The combined results of these studies suggest several things. First, it appears that either excessively long, or excessively short, adaptation cycles can limit the effectiveness of adaptive automation in enhancing operator performance of both primary flight and monitoring tasks. Second, occasional brief reversions to manual control can counter some of the monitoring inefficiency typically associated with long cycle automation, and further, that benefits of such reversions can be sustained for some time after return to automated control. Third, no evidence was found that the benefits of such reversions depend on the adaptive logic by which long-cycle adaptive switches are triggered.

Hilburn, Brian↗
NASA NTRS1988

Adaptive independent joint control of manipulators - Theory and experiment

The author presents a simple decentralized adaptive control scheme for multijoint robot manipulators based on the independent joint control concept. The proposed control scheme for each joint consists of a PID (proportional integral and differential) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. The static and dynamic couplings that exist between the joint motions are compensated by the adaptive independent joint controllers while ensuring trajectory tracking. The proposed scheme is implemented on a MicroVAX II computer for motion control of the first three joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite strongly coupled, highly nonlinear joint dynamics. The results confirm that the proposed decentralized adaptive control of manipulators is feasible, in spite of strong interactions between joint motions. The control scheme presented is computationally very fast and is amenable to parallel processing implementation within a distributed computing architecture, where each joint is controlled independently by a simple algorithm on a dedicated microprocessor.

Seraji, H.↗
NASA NTRS1992

Self-tuning control of attitude and momentum management for the Space Station

This paper presents a hybrid state-space self-tuning design methodology using dual-rate sampling for suboptimal digital adaptive control of attitude and momentum management for the Space Station. This new hybrid adaptive control scheme combines an on-line recursive estimation algorithm for indirectly identifying the parameters of a continuous-time system from the available fast-rate sampled data of the inputs and states and a controller synthesis algorithm for indirectly finding the slow-rate suboptimal digital controller from the designed optimal analog controller. The proposed method enables the development of digitally implementable control algorithms for the robust control of Space Station Freedom with unknown environmental disturbances and slowly time-varying dynamics.

Shieh, L. S.↗
DOE OSTI2025

Unified ELM Suppression on KSTAR and DIII-D via Adaptive Feedback Control Strategies

This paper reports on the extension of our amplitude-based resonant magnetic perturbation (RMP) edge localized mode (ELM) controller to support phasing control (relative toroidal phases of RMP waveforms between rows of coils), multiple toroidal mode numbers, and new ‘jump’ and ‘probing’ strategies, all deployed on KSTAR and DIII-D. By treating the control algorithm as device-independent and adjusting only the real-time interfaces to sensors and power supplies, we have confirmed that the same finite state machine—based feedback logic can be ported between machines with minor modifications. In experiments using n = 2 RMPs on KSTAR and n = 3 on DIII-D, the controller successfully modulated RMP amplitudes in real time to sustain ELM suppression while minimizing confinement degradation. Phasing control broadened the suppression window, as it permitted the system to avoid locked-mode regions and safely access ELM-free conditions. A rotating RMP phasing scheme, integrated into the same framework, distributes divertor heat loads more uniformly, making it a promising strategy for protecting plasma-facing components during long discharges. New ‘jump’ and ‘probing’ techniques demonstrate the possibility for the controller to preempt imminent ELMs and refine the minimum required RMP amplitude without returning to ELMy conditions. Taken together, these upgrades enable extended ELM-free operation while mitigating confinement degradation, providing a practical framework for real-time ELM control in future high-performance tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1979

The dual-momentum control device for large space systems

The dual-momentum control device being studied for large spacecraft consists of two counter-rotating rings, each designated as an annular momentum control device (AMCD). For large rings, flexibility is appreciable and it becomes necessary to account for the distributed nature of the rings in the design of the magnetic bearing controllers. Also, ring behavior is unpredictably sensitive to ring temperature, spin rate, manufacturing imperfections, and other variables. For that reason, an adaptive control system is being sought for ring stabilization and maneuvering. This paper details an original adaptive control methodology for distributed parameter systems and illustrates this technique by application to AMCD stabilization.

Montgomery, R. C.↗