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Sparks, Dean W., Jr.

Publications and source records attributed to Sparks, Dean W., Jr..

12 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Crew Exploration Vehicle Ascent Abort Overview

One of the primary design drivers for NASA's Crew Exploration Vehicle (CEV) is to ensure crew safety. Aborts during the critical ascent flight phase require the design and operation of CEV systems to escape from the Crew Launch Vehicle and return the crew safely to the Earth. To accomplish this requirement of continuous abort coverage, CEV ascent abort modes are being designed and analyzed to accommodate the velocity, altitude, atmospheric, and vehicle configuration changes that occur during ascent. The analysis involves an evaluation of the feasibility and survivability of each abort mode and an assessment of the abort mode coverage. These studies and design trades are being conducted so that more informed decisions can be made regarding the vehicle abort requirements, design, and operation. This paper presents an overview of the CEV, driving requirements for abort scenarios, and an overview of current ascent abort modes. Example analysis results are then discussed. Finally, future areas for abort analysis are addressed.

Davidson, John B., Jr.↗
NASA NTRS2007

Crew Exploration Vehicle Launch Abort Controller Performance Analysis

This paper covers the simulation and evaluation of a controller design for the Crew Module (CM) Launch Abort System (LAS), to measure its ability to meet the abort performance requirements. The controller used in this study is a hybrid design, including features developed by the Government and the Contractor. Testing is done using two separate 6-degree-of-freedom (DOF) computer simulation implementations of the LAS/CM throughout the ascent trajectory: 1) executing a series of abort simulations along a nominal trajectory for the nominal LAS/CM system; and 2) using a series of Monte Carlo runs with perturbed initial flight conditions and perturbed system parameters. The performance of the controller is evaluated against a set of criteria, which is based upon the current functional requirements of the LAS. Preliminary analysis indicates that the performance of the present controller meets (with the exception of a few cases) the evaluation criteria mentioned above.

Sparks, Dean W., Jr.↗
NASA NTRS1998

Neural Networks for Rapid Design and Analysis

Artificial neural networks have been employed for rapid and efficient dynamics and control analysis of flexible systems. Specifically, feedforward neural networks are designed to approximate nonlinear dynamic components over prescribed input ranges, and are used in simulations as a means to speed up the overall time response analysis process. To capture the recursive nature of dynamic components with artificial neural networks, recurrent networks, which use state feedback with the appropriate number of time delays, as inputs to the networks, are employed. Once properly trained, neural networks can give very good approximations to nonlinear dynamic components, and by their judicious use in simulations, allow the analyst the potential to speed up the analysis process considerably. To illustrate this potential speed up, an existing simulation model of a spacecraft reaction wheel system is executed, first conventionally, and then with an artificial neural network in place.

Sparks, Dean W., Jr.↗
NASA NTRS1998

Design of Neural Networks for Fast Convergence and Accuracy

A novel procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed to provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component spacecraft design changes and measures of its performance. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The design algorithm attempts to avoid the local minima phenomenon that hampers the traditional network training. A numerical example is performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗
NASA NTRS1998

Fault Accommodation in Control of Flexible Systems

New synthesis techniques for the design of fault accommodating controllers for flexible systems are developed. Three robust control design strategies, static dissipative, dynamic dissipative and mu-synthesis, are used in the approach. The approach provides techniques for designing controllers that maximize, in some sense, the tolerance of the closed-loop system against faults in actuators and sensors, while guaranteeing performance robustness at a specified performance level, measured in terms of the proximity of the closed-loop poles to the imaginary axis (the degree of stability). For dissipative control designs, nonlinear programming is employed to synthesize the controllers, whereas in mu-synthesis, the traditional D-K iteration is used. To demonstrate the feasibility of the proposed techniques, they are applied to the control design of a structural model of a flexible laboratory test structure.

Maghami, Peiman G.↗
NASA NTRS1997

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗
NASA NTRS1993

CSI Flight Computer System and experimental test results

This paper describes the CSI Computer System (CCS) and the experimental tests performed to validate its functionality. This system is comprised of two major components: the space flight qualified Excitation and Damping Subsystem (EDS) which performs controls calculations; and the Remote Interface Unit (RIU) which is used for data acquisition, transmission, and filtering. The flight-like RIU is the interface between the EDS and the sensors and actuators positioned on the particular structure under control. The EDS and RIU communicate over the MIL-STD-1553B, a space flight qualified bus. To test the CCS under realistic conditions, it was connected to the Phase-0 CSI Evolutionary Model (CEM) at NASA Langley Research Center. The following schematic shows how the CCS is connected to the CEM. Various tests were performed which validated the ability of the system to perform control/structures experiments.

Sparks, Dean W., Jr.↗
NASA NTRS1993

Piezoelectric devices for vibration suppression: Modeling and application to a truss structure

For a space structure assembled from truss members, an effective way to control the structure may be to replace the regular truss elements by active members. The active members play the role of load carrying elements as well as actuators. A piezo strut, made of a stack of piezoceramics, may be an ideal active member to be integrated into a truss space structure. An electrically driven piezo strut generates a pair of forces, and is considered as a two-point actuator in contrast to a one-point actuator such as a thruster or a shaker. To achieve good structural vibration control, sensing signals compatible to the control actuators are desirable. A strain gage or a piezo film with proper signal conditioning to measure member strain or strain rate, respectively, are ideal control sensors for use with a piezo actuator. The Phase 0 CSI Evolutionary Model (CEM) at NASA Langley Research Center used cold air thrusters as actuators to control both rigid body motions and flexible body vibrations. For the Phase 1 and 2 CEM, it is proposed to use piezo struts to control the flexible modes and thrusters to control the rigid body modes. A tenbay truss structure with active piezo struts is built to study the modeling, controller designs, and experimental issues. In this paper, the tenbay structure with piezo active members is modelled using an energy method approach. Decentralized and centralized control schemes are designed and implemented, and preliminary analytical and experimental results are presented.

Won, Chin C.↗
NASA NTRS1992

CSI computer system/remote interface unit acceptance test results

The validation tests conducted on the Control/Structures Interaction (CSI) Computer System (CCS)/Remote Interface Unit (RIU) is discussed. The CCS/RIU consists of a commercially available, Langley Research Center (LaRC) programmed, space flight qualified computer and a flight data acquisition and filtering computer, developed at LaRC. The tests were performed in the Space Structures Research Laboratory (SSRL) and included open loop excitation, closed loop control, safing, RIU digital filtering, and RIU stand alone testing with the CSI Evolutionary Model (CEM) Phase-0 testbed. The test results indicated that the CCS/RIU system is comparable to ground based systems in performing real-time control-structure experiments.

Sparks, Dean W., Jr.↗
NASA NTRS1989

A survey of experiments and experimental facilities for active control of flexible structures

A brief survey of large space structure control related experiments and facilities was presented. This survey covered experiments performed before and up to 1982, and those of the present period (1982-...). Finally, the future planned experiments and facilities in support of the control-structure interaction (CSI) program were reported. It was stated that new, improved ground test facilities are needed to verify the new CSI design techniques that will allow future space structures to perform planned NASA missions.

Sparks, Dean W., Jr.↗
NASA NTRS1989

A survey of experiments and experimental facilities for control of flexible structures

This paper presents a survey of U.S. ground experiments and facilities dedicated to the study of active control of flexible structures. The facilities will be briefly described in terms of capability, configuration, size and instrumentation. Topics on the experiments include vibration suppression, slewing and system identification. Future research directions, particularly of the NASA Langley Research Center's Controls/Structures Interaction (CSI) ground test program, will be discussed.

Sparks, Dean W., Jr.↗