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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Stability Limits of a PD Controller for a Flywheel Supported on Rigid Rotor and Magnetic Bearings

Active magnetic bearings are used to provide a long-life, low-loss suspension of a high-speed flywheel rotor. This paper describes a modeling effort used to understand the stability boundaries of the PD controller used to control the active magnetic bearings on a high speed test rig. Limits of stability are described in terms of allowable stiffness and damping values which result in stable levitation of the nonrotating rig. Small signal stability limits for the system is defined as a nongrowth in vibration amplitude of a small disturbance. A simple mass-force model was analyzed. The force resulting from the magnetic bearing was linearized to include negative displacement stiffness and a current stiffness. The current stiffness was then used in a PD controller. The phase lag of the control loop was modeled by a simple time delay. The stability limits and the associated vibration frequencies were measured and compared to the theoretical values. The results show a region on stiffness versus damping plot that have the same qualitative tendencies as experimental measurements. The resulting stability model was then extended to a flywheel system. The rotor dynamics of the flywheel was modeled using a rigid rotor supported on magnetic bearings. The equations of motion were written for the center of mass and a small angle linearization of the rotations about the center of mass. The stability limits and the associated vibration frequencies were found as a function of nondimensional magnetic bearing stiffness and damping and nondimensional parameters of flywheel speed and time delay.

Kascak, Albert F.↗
DOE OSTI2015

Accessing conjugated polymers with precisely controlled heterobisfunctional chain ends via post-polymerization modification of the OTf group and controlled Pd(0)/t-Bu 3 P-catalyzed Suzuki cross-coupling polymerization

In this study, a general strategy toward the synthesis of well-defined conjugated polymers with controlled heterobisfunctional chain ends via combination of controlled Pd(0)/t-Bu 3 P Suzuki cross-coupling polymerization with the post-polymerization modification of the triflate (OTf) group was disclosed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Controlled Pd(0)/t Bu3P Catalyzed Suzuki Cross-Coupling Polymerization of AB-Type Monomers with ArPd(t Bu3P)X or Pd2(dba)3/t Bu3P/ArX as the Initiator

The synthesis of well-defined and functionalized conjugated polymers, which are essential in the development of efficient organic electronics, through Suzuki cross-coupling polymerizations has been a challenging task. We developed controlled Pd(0)/t-Bu3P-catalyzed Suzuki cross-coupling polymerizations of AB-type monomers via the chain-growth mechanism with a series of in situ generated ArPd(t-Bu3P)X (X = I, Br, Cl) complexes as initiators. Among them, the combinations of Pd2(dba)3/t-Bu3P/p-BrC6H4I, Pd2(dba)3/t-Bu3P/p-BrC6H4CH2OH and Pd2(dba)3/t-Bu3P/p-PhCOC6H4Br were identified as highly robust initiator systems, resulting in polymers with predictable molecular weight and narrow polydispersity (PDI~1.13-1.20). In addition, Pd2(dba)3/t-Bu3P/p-BrC6H4CH2OH and Pd2(dba)3/t-Bu3P/p-PhCOC6H4Br initiator systems afforded functional polymers with >95% fidelity. Our results paved the road to access well-defined conjugated polymers, including conjugated polymers with complex polymer architectures such as block copolymers and branch copolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Decoupling the Geometric Parameters of Shape-Controlled Pd Nanocatalysts

The structural features of metal nanoparticles such as crystallite size and shape are important to catalytic activity and selectivity. Thus, correlating the performance of metal nanocatalysts to these structural features is important to understanding and designing better catalysts. The size and shape effects of Pd nanocrystals are examined as they are applied as semihydrogenation catalysts. Seed-mediated growth methods were used to achieve samples composed of different-sized {100}-terminated Pd nanocubes and {111}-terminated Pd nanoctahedra, which served as model systems to evaluate the role of surface structure to activity and selectivity. The size of the nanocrystals was easily tuned by controlling the amount of metal deposited per seed. The selection of capping agent provided a means of manipulating the final shape of the nanocrystals. Finally, the catalysis results from this study will facilitate the decoupling of the size and shape contributions to the geometric parameters of Pd nanocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Twin Proliferation and Prolongation under Kinetic Control: Pd–Au Janus Icosahedra versus Pd@Au Core–Shell Starfishes

Heterogeneous bimetallic nanocrystals featuring explicit spatial configurations and abundant twin defects can simultaneously enable geometric and ligand effects to enhance catalytic and photonic applications. Herein, we report two growth patterns of Au atoms on penta-twinned Pd decahedra, involving twin proliferation to generate asymmetric Pd–Au Janus icosahedra and twin elongation to produce anisotropic Pd@Au core–shell starfishes, respectively. Mechanistic analysis indicates that the injection rate determines the lower-limit number (n low ) of Au(III) ions in the steady state and thus controls the growth pattern. When n low ≤ 5.5, the kinetic rate is slow enough to initiate asymmetrical one-side growth but fast enough to outpace surface diffusion; Au tetrahedral subunits are successively proliferated along the axial $\langle$110$\rangle$ direction of Pd decahedra to form Pd–Au Janus icosahedra. Composed of five Pd and 15 Au tetrahedral subunits, such a heterogeneous icosahedron supports high (2.2 GPa) tensile strain and high strain difference up to +21.9%. In contrast, when n low > 5.5, the fast reduction kinetics promotes symmetric growth with inadequate surface diffusion. As such, Au atoms are laterally deposited along five high-indexed $\langle$211$\rangle$ ridges of Pd decahedra to generate concave Pd@Au core–shell starfishes with tunable sizes (28–40 nm), twin elongation ratios (33.82–162.08%), and lattice expansion ratios (8.82–20.10%).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nanoscale wetting controls reactive Pd ensembles in synthesis of dilute PdAu alloy catalysts

The performance of bimetallic dilute alloy catalysts is largely determined by the size of minority metal ensembles on the nanoparticle surface. By analyzing the synthesis of catalysts comprising Pd 8 Au 92 nanoparticles supported on silica using surface-sensitive techniques, we report that whether Pd overgrowth occurs before or after Au nanoparticle deposition onto the support controls the surface Pd ensemble size and abundance. These differences in Pd ensembles influence catalytic reactivity in H 2 –D 2 isotope exchange and benzaldehyde hydrogenation, which, in correlation with theoretical calculations, is used to elucidate the active site(s) in each reaction. To clarify how the synthetic sequence controls the formation of Pd ensembles, we combine numerical wetting calculations and molecular dynamics simulations (with a machine-learned force field) to visualize Pd deposition and migration on the nanoparticle surface, respectively. Our results suggest that the nanoparticle–support interface restricts nanoparticle accessibility to Pd deposition, which consequently controls the Pd ensemble size, illustrating the critical role of nanoscale wetting phenomena during bimetallic catalyst preparation.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Multivariable PID Controller For Robotic Manipulator

Gains updated during operation to cope with changes in characteristics and loads. Conceptual multivariable controller for robotic manipulator includes proportional/derivative (PD) controller in inner feedback loop, and proportional/integral/derivative (PID) controller in outer feedback loop. PD controller places poles of transfer function (in Laplace-transform space) of control system for linearized mathematical model of dynamics of robot. PID controller tracks trajectory and decouples input and output.

Seraji, Homayoun↗
NASA NTRS1987

A tuning scheme for proportional-and-derivative controllers

A simple way of tuning usual proportional-and-derivative (PD) controllers is presented. The tuning is devised so that the closed-loop system has a speed of response near that of time-optimal bang-bang control during a large portion of the transient period. When the system is near the desired equilibrium it behaves linearly, and thus avoids the problem of being overly sensitive to the disturbances and noise. The idea is rather intuitive. Unlike dual-mode control, the plant is controlled throughout by a PD controller. Numerical results are included.

Su, Renjeng↗
NASA NTRS2010

Lunar Reconnaissance Orbiter (LRO) Thruster Control Mode Design and Flight Experience

National Aeronautics and Space Administration s (NASA) Goddard Space Flight Center (GSFC) in Greenbelt, MD, designed, built, tested, and launched the Lunar Reconnaissance Orbiter (LRO) from Cape Canaveral Air Force Station on June 18, 2009. The LRO spacecraft is the first operational spacecraft designed to support NASA s return to the Moon, as part of the Vision for Space Exploration. LRO was launched aboard an Atlas V 401 launch vehicle into a direct insertion trajectory to the Moon. Twenty-four hours after separation the propulsion system was used to perform a mid-course correction maneuver. Four days after the mid-course correction a series of propulsion maneuvers were executed to insert LRO into its commissioning orbit. The commission period lasted eighty days and this followed by a second set of thruster maneuvers that inserted LRO into its mission orbit. To date, the spacecraft has been gathering invaluable data in support of human s future return to the moon. The LRO Attitude Control Systems (ACS) contains two thruster based control modes: Delta-H and Delta-V. The design of the two controllers are similar in that they are both used for 3-axis control of the spacecraft with the Delta-H controller used for momentum management and the Delta-V controller used for orbit adjust and maintenance maneuvers. In addition to the nominal purpose of the thruster modes, the Delta-H controller also has the added capability of performing a large angle slew maneuver. A suite of ACS components are used by the thruster based control modes, for both initialization and control. For initialization purposes, a star tracker or the Kalman Filter solution is used for providing attitude knowledge and upon entrance into the thruster based control modes attitude knowledge is provided via rate propagation using a inertial reference unit (IRU). Rate information for the controller is also supplied by the IRU. Three-axis control of the spacecraft in the thruster modes is provided by eight 5-lbf class attitude control thrusters configured in two sets of four thrusters for redundancy purposes. Four additional 20-lbf class thrusters configured in two sets of two thrusters are used for Lunar Orbit Insertion maneuvers. The propulsion system is one the few systems on-board the LRO spacecraft that has built in redundancy. The Delta-H controller consists of a Proportional-Derivative (PD) controller with a structural filter on the thrusters and a Proportional controller on the reaction wheels. The PD control that employs the thrusters is used for attitude and rate control. The Proportional controller on the reaction wheels is used for commanding the wheels to a new momentum state. The ground commands used for the Delta-H controller are the system momentum vector, reaction wheel momentum, maximum expected command time, and which set of attitude control thrusters to use. The ability to command both the system momentum vector and reaction wheel momentum in the Delta-H controller provides both a capability and an additional source of operator error. Large angle slews via the Delta-H controller is achievable via this commands because these commands are used for the exit mode criteria. Setting these commands to non-consistent values prevents the mode from exiting nominally.

Hsu, Oscar C.↗
DOE OSTI2018

Improved sensing of vertical velocity for vertical position control using loop voltage signals on EAST

Vertical position control of shaped plasma is critical for all elongated tokamaks to achieve safe and stable plasma discharge. In EAST, the in-vessel coil (IC) is employed for fast control of plasma vertical motion which power supply capabilities limits the controllability of vertical instability. Moreover, adequate signal-to-noise ratio of vertical position measurement can also realize an improvement in vertical control. In EAST, plasma vertical position Z p is produced nearly by all integrated magnetics, fast Z error signal is obtained by filtering from Zp. Then this fast Z error and its derivative term (dz/dt) are controlled by IC with a separate PD controller. Yet, it has a low signal-to-noise ratio which limits the gains that can be used successfully in the PD control loops. To provide less noisy dz/dt signal, the successful use of multiple up/down loop voltage pairs instead of derivative of z derived from magnetic probe signals will be discussed. Experiment show that even a single pair of loop voltage signal has better signal-to-noise ratio than differentiation of Z p . In addition, flux loop pickup signals from the IC current are also measured with series of positive and negative IC current pulses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2018

Dynamics and Control of a Tethered Enhanced Gravity Tractor Performing Asteroid Deflection

The dynamics and control of an Enhanced Gravity Tractor (EGT) augmented with a tether for deflecting an asteroid are studied. A conventional EGT consists of collected asteroidal mass collocated with the spacecraft. Because of the presence of a tether, the collected mass is placed where the EGT would have been without a tether, and the spacecraft is placed farther away from the asteroid. Doing so improves the fuel efficiency and safety margin of the EGT operation without significantly sacrificing the gravitational attraction between the asteroid and the EGT. The tether is modeled as a series of particles connected by spring-dashpot systems. Physical properties of the tether are selected to be similar to those of the SPECTRA-1000, Kevlar-29, and Kevlar-49 fibers. It is assumed that control is applied only to the spacecraft, and there is no active control associated with the collected mass. A Proportional-Derivative (PD) controller is employed to maintain the spacecraft and the collected mass at desired positions relative to the asteroid. Numerical simulations of tethered EGT operations at 2008 EV5, Itokawa, Apophis, and a fictitious ellipsoidal asteroid are performed. It is demonstrated that a PD controller is capable of accomplishing the control objectives. The gravity gradient and the control force keep the tether stretched throughout a normal tethered EGT operation, and the load on the tether is well within the design limit of the tether material. While including multiple particles in the tether model is essential in capturing details of tether vibration, the number of particles does not significantly affect the motions of the collected mass and the spacecraft. In addition, the distance from the asteroid mass center to the collected mass should be chosen judiciously in the case of a rotating slender asteroid; some distance ranges should be avoided as excessive lateral oscillations can be excited by resonance between the asteroid rotation and tether pendular motion.

Shen, Haijun↗
NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗
NASA NTRS1991

A multivariable control scheme for robot manipulators

The article puts forward a simple scheme for multivariable control of robot manipulators to achieve trajectory tracking. The scheme is composed of an inner loop stabilizing controller and an outer loop tracking controller. The inner loop utilizes a multivariable PD controller to stabilize the robot by placing the poles of the linearized robot model at some desired locations. The outer loop employs a multivariable PID controller to achieve input-output decoupling and trajectory tracking. The gains of the PD and PID controllers are related directly to the linearized robot model by simple closed-form expressions. The controller gains are updated on-line to cope with variations in the robot model during gross motion and for payload change. Alternatively, the use of high gain controllers for gross motion and payload change is discussed. Computer simulation results are given for illustration.

Tarokh, M.↗
DOE OSTI2023

Fluorine spillover for ceria- vs silica-supported palladium nanoparticles: A MD study using machine learning potentials

Supported metallic nanoparticles play a central role in catalysis. However, predictive modeling is particularly challenging due to the structural and dynamic complexity of the nanoparticle and its interface with the support, given that the sizes of interest are often well beyond those accessible via traditional ab initio methods. With recent advances in machine learning, it is now feasible to perform MD simulations with potentials retaining near-density-functional theory (DFT) accuracy, which can elucidate the growth and relaxation of supported metal nanoparticles, as well as reactions on those catalysts, at temperatures and time scales approaching those relevant to experiments. Furthermore, the surfaces of the support materials can also be modeled realistically through simulated annealing to include effects such as defects and amorphous structures. We study the adsorption of fluorine atoms on ceria and silica supported palladium nanoparticles using machine learning potential trained by DFT data using the DeePMD framework. We show defects on ceria and Pd/ceria interfaces are crucial for the initial adsorption of fluorine, while the interplay between Pd and ceria and the reverse oxygen migration from ceria to Pd control spillover of fluorine from Pd to ceria at later stages. In contrast, silica supports do not induce fluorine spillover from Pd particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Stabilization of a Quadrotor With Uncertain Suspended Load Using Sliding Mode Control

The stability and trajectory control of a quadrotor carrying a suspended load with a fixed known mass has been extensively studied in recent years. However, the load mass is not always known beforehand in practical applications. This mass uncertainty brings uncertain disturbances to the quadrotor system, causing existing controllers to have a worse performance or to be collapsed. To improve the quadrotor's stability in this situation, we investigate the impacts of the uncertain load mass on the quadrotor. By comparing the simulation results of two controllers -- the proportional-derivative (PD) controller and the sliding mode controller (SMC) driven by a sliding mode disturbance of observer (SMDO), the quadrotor's performance is verified to be worse as the uncertainty increases. The simulation results also show a controller with stronger robustness against disturbances is better for practical applications.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1987

A universal six-joint robot controller

A general purpose six-axis robotic manipulator controller was designed and implemented to serve as a research tool for the investigation of the practical and theoretical aspects of various control strategies in robotics. A 80286-based Intel System 310 running the Xenix operating servo software as well as the higher level software (e.g., kinematics and path planning) were employed. A Multibus compatible interface board was designed and constructed to handle I/O signals from the robot manipulator's joint motors. From the design point of view, the universal controller is capable of driving robot manipulators equipped with D.C. joint motors and position optical encoders. To test its functionality, the controller is connected to the joint motor D.C. power amplifier of a PUMA 560 arm bypassing completely the manufacturer-supplied Unimation controller. A controller algorithm consisting of local PD control laws was written and installed into the Xenix operating system. Additional software drivers were implemented to allow application programs access to the interface board. All software was written in the C language.

Bihn, D. G.↗