Optimal active vibration absorber: Design and experimental results

An optimal active vibration absorber can provide guaranteed closed-loop stability and control for large flexible space structures with collocated sensors/actuators. The active vibration absorber is a second-order dynamic system which is designed to suppress any unwanted structural vibration. This can be designed with minimum knowledge of the controlled system. Two methods for optimizing the active vibration absorber parameters are illustrated: minimum resonant amplitude and frequency matched active controllers. The Controls-Structures Interaction Phase-1 Evolutionary Model at NASA LaRC is used to demonstrate the effectiveness of the active vibration absorber for vibration suppression. Performance is compared numerically and experimentally using acceleration feedback

Dynamic analysis of the GEOS satellite

The assumed modes method is used to investigate the stability of the GEOS satellite. The system is discretized by representing the continuous displacement by finite series of space-dependent admissible functions multiplied by time-dependent generalized coordinates. The spatial dependence is eliminated by integration over the elastic domains, so that the testing functional reduces to a testing function. The sign properties of the testing function are then tested and the equilibrium defined as nontrivial. In considering the stability of small motions about nontrivial equilibrium, it is shown that if the analysis performed by ignoring the motion of the mass center indicates stability, then the system remains stable if the motion of the mass center is included

A velocity command stepper motor for CSI application

The application of linear force actuators for vibration suppression of flexible structures has received much attention in recent years. A linear force actuator consists of a movable mass that is restrained such that its motion is linear. By application of a force to the mass, an equal and opposite reaction force can be applied to a structure. The use of an industrial linear stepper motor as a reaction mass actuator is described. With the linear stepper motor mounted on a simple test beam and the NASA Mini-Mast, output feedback of acceleration or displacement are used to augment the structural damping of the test articles. Significant increases in damping were obtained for both the test beam and the Mini-Mast

Self-consistent approach for the quantum confined Stark effect in shallow quantum wells

A computationally efficient, self-consistent complex scaling approach to calculating characteristics of excitons in an external electric field in quantum wells is introduced. The method allows one to extract the resonance position as well as the field-induced broadening for the exciton resonance. For the case of strong confinement the trial function is represented in factorized form. The corresponding coupled self-consistent equations, which include the effective complex potentials, are obtained. The method is applied to the shallow quantum well. It is shown that in this case the real part of the effective exciton potential is insensitive to changes of external electric field up to the ionization threshold, while the imaginary part has non-analytical field dependence and small for moderate electric fields. This allows one to express the exciton quasi-energy at some field through the renormalized expression for the zero-field bound state.Comment: 13 pages, RevTeX4, 6 figure

Space robotics: Recent accomplishments and opportunities for future research

The Langley Guidance, Navigation, and Control Technical Committee (GNCTC) was one of six technical committees created in 1991 by the Chief Scientist, Dr. Michael F. Card. During the kickoff meeting Dr. Card charged the chairmen to: (1) establish a cross-Center committee; (2) support at least one workshop in a selected discipline; and (3) prepare a technical paper on recent accomplishments in the discipline and on opportunities for future research. The Guidance, Navigation, and Control Committee was formed and selected for focus on the discipline of Space robotics. This report is a summary of the committee's assessment of recent accomplishments and opportunities for future research. The report is organized as follows. First is an overview of the data sources used by the committee. Next is a description of technical needs identified by the committee followed by recent accomplishments. Opportunities for future research ends the main body of the report. It includes the primary recommendation of the committee that NASA establish a national space facility for the development of space automation and robotics, one element of which is a telerobotic research platform in space. References 1 and 2 are the proceedings of two workshops sponsored by the committee during its June 1991, through May 1992 term. The focus of the committee for the June 1992 - May 1993 term will be to further define to the recommended platform in space and to add an additional discipline which includes aircraft related GN&C issues. To the latter end members performing aircraft related research will be added to the committee. (A preliminary assessment of future opportunities in aircraft-related GN&C research has been included as appendix A.

Quasiparticle dynamics and phonon softening in FeSe superconductors

Quasiparticle dynamics of FeSe single crystals revealed by dual-color transient reflectivity measurements ({\Delta}R/R) provides unprecedented information on Fe-based superconductors. The amplitude of fast component in {\Delta}R/R clearly tells a competing scenario between spin fluctuations and superconductivity. Together with the transport measurements, the relaxation time analysis further exhibits anomalous changes at 90 K and 230 K. The former manifests a structure phase transition as well as the associated phonon softening. The latter suggests a previously overlooked phase transition or crossover in FeSe. The electron-phonon coupling constant {\lambda} is found to be 0.16, identical to the value of theoretical calculations. Such a small {\lambda} demonstrates an unconventional origin of superconductivity in FeSe.Comment: Final published version; 5 pages; 4 figure

Recent Enhancements to the Development of CFD-Based Aeroelastic Reduced-Order Models

Recent enhancements to the development of CFD-based unsteady aerodynamic and aeroelastic reduced-order models (ROMs) are presented. These enhancements include the simultaneous application of structural modes as CFD input, static aeroelastic analysis using a ROM, and matched-point solutions using a ROM. The simultaneous application of structural modes as CFD input enables the computation of the unsteady aerodynamic state-space matrices with a single CFD execution, independent of the number of structural modes. The responses obtained from a simultaneous excitation of the CFD-based unsteady aerodynamic system are processed using system identification techniques in order to generate an unsteady aerodynamic state-space ROM. Once the unsteady aerodynamic state-space ROM is generated, a method for computing the static aeroelastic response using this unsteady aerodynamic ROM and a state-space model of the structure, is presented. Finally, a method is presented that enables the computation of matchedpoint solutions using a single ROM that is applicable over a range of dynamic pressures and velocities for a given Mach number. These enhancements represent a significant advancement of unsteady aerodynamic and aeroelastic ROM technology

IK-FA, a new heuristic inverse kinematics solver using firefly algorithm

In this paper, a heuristic method based on Firefly Algorithm is proposed for inverse kinematics problems in articulated robotics. The proposal is called, IK-FA. Solving inverse kinematics, IK, consists in finding a set of joint-positions allowing a specific point of the system to achieve a target position. In IK-FA, the Fireflies positions are assumed to be a possible solution for joints elementary motions. For a robotic system with a known forward kinematic model, IK-Fireflies, is used to generate iteratively a set of joint motions, then the forward kinematic model of the system is used to compute the relative Cartesian positions of a specific end-segment, and to compare it to the needed target position. This is a heuristic approach for solving inverse kinematics without computing the inverse model. IK-FA tends to minimize the distance to a target position, the fitness function could be established as the distance between the obtained forward positions and the desired one, it is subject to minimization. In this paper IK-FA is tested over a 3 links articulated planar system, the evaluation is based on statistical analysis of the convergence and the solution quality for 100 tests. The impact of key FA parameters is also investigated with a focus on the impact of the number of fireflies, the impact of the maximum iteration number and also the impact of (a, ß, ¿, d) parameters. For a given set of valuable parameters, the heuristic converges to a static fitness value within a fix maximum number of iterations. IK-FA has a fair convergence time, for the tested configuration, the average was about 2.3394 × 10-3 seconds with a position error fitness around 3.116 × 10-8 for 100 tests. The algorithm showed also evidence of robustness over the target position, since for all conducted tests with a random target position IK-FA achieved a solution with a position error lower or equal to 5.4722 × 10-9.Peer ReviewedPostprint (author's final draft

Discriminative training for Convolved Multiple-Output Gaussian processes

Multi-output Gaussian processes (MOGP) are probability distributions over vector-valued functions, and have been previously used for multi-output regression and for multi-class classification. A less explored facet of the multi-output Gaussian process is that it can be used as a generative model for vector-valued random fields in the context of pattern recognition. As a generative model, the multi-output GP is able to handle vector-valued functions with continuous inputs, as opposed, for example, to hidden Markov models. It also offers the ability to model multivariate random functions with high dimensional inputs. In this report, we use a discriminative training criteria known as Minimum Classification Error to fit the parameters of a multi-output Gaussian process. We compare the performance of generative training and discriminative training of MOGP in emotion recognition, activity recognition, and face recognition. We also compare the proposed methodology against hidden Markov models trained in a generative and in a discriminative way