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At least 469 records · Page 26

Dynamic sensing of 6-axis external force and moment applied to a robot end

A dynamic force sensing method is proposed for a robot manipulator. A 6-axis wrist force sensor which is commonly used for robot force sensing does not take the direct measurement of the force and moment applied to an end effector externally from the environment of the manipulator, but takes the resultant of the gravity, the inertial force and moment on the end effector, and the external force and moment. The separation of gravitational and inertial force and moment from the measurement of the force sensor is crucial to achieving dynamically accurate force sensing and fast manipulator motion under force feedback control. A mathematical model is derived for the force sensing process and the separation of the force and moment as a nonlinear optimal state estimation problem formulated. Then an approximate solution is given using extended Kalman filtering techniques.

Yokota, Masaru Uchiyama↗

Performances Of Fixed-Lag Phase-Smoothing Algorithms

Report discusses performances of fixed-lag nonlinear smoothing algorithms applied to estimation of phase and frequency of sinusoidal carrier signal with process phase noise and additive observation phase noise. Algorithm of type considered functions as suboptimal filter operating on received signal. Algorithm developed for system in which signal sampled at discrete times. Process noise assumed to be Gaussian with zero mean and independent of observation noise. Nonlinear smoothing equations derived in customary matrix-and-vector forms.

Kumar, Rajendra↗

Lasers '92; Proceedings of the International Conference on Lasers and Applications, 15th, Houston, TX, Dec. 7-10, 1992

Papers from the conference are presented, and the topics covered include the following: x-ray lasers, excimer lasers, chemical lasers, high power lasers, blue-green lasers, dye lasers, solid state lasers, semiconductor lasers, gas and discharge lasers, carbon dioxide lasers, ultrafast phenomena, nonlinear optics, quantum optics, dynamic gratings and wave mixing, laser radar, lasers in medicine, optical filters and laser communication, optical techniques and instruments, laser material interaction, and industrial and manufacturing applications.

Wang, Charles P.↗

Nonlinear optics and crystalline whispering gallery mode resonators

We report on our recent results concerning fabrication of high-Q whispering gallery mode (WGM) crystalline resonators, and discuss some possible applications of lithium niobate WGM resonators in nonlinear optics and photonics. In particular, we demonstrate experimentally a tunable third-order optical filter fabricated from the three metalized resonators; and report observation of parametric frequency dobuling in a WGM resonator made of periodically poled lithium niobate (PPLN).

whispering gallery mode↗

Asymptotic consistency of the WSINDy algorithm in the limit of continuum data

In this work we study the asymptotic consistency of the weak-form sparse identification of nonlinear dynamics algorithm (WSINDy) in the identification of differential equations from noisy samples of solutions. We prove that the WSINDy estimator is unconditionally asymptotically consistent for a wide class of models that includes the Navier–Stokes, Kuramoto–Sivashinsky and Sine–Gordon equations. We thus provide a mathematically rigorous explanation for the observed robustness to noise of weak-form equation learning. Conversely, we also show that, in general, the WSINDy estimator is only conditionally asymptotically consistent, yielding discovery of spurious terms with probability one if the noise level exceeds a critical threshold σ c . We provide explicit bounds on σ c in the case of Gaussian white noise and we explicitly characterize the spurious terms that arise in the case of trigonometric and/or polynomial libraries. Furthermore, we show that, if the data is suitably denoised (a simple moving average filter is sufficient), then asymptotic consistency is recovered for models with locally-Lipschitz, polynomial-growth nonlinearities. Our results reveal important aspects of weak-form equation learning, which may be used to improve future algorithms. We demonstrate our findings numerically using the Lorenz system, the cubic oscillator, a viscous Burgers-growth model and a Kuramoto–Sivashinsky-type high-order PDE.

asymptotic consistency↗

Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Theory-Guided Autoencoders

Data assimilation is a Bayesian inference process that obtains an enhanced understanding of a physical system of interest by fusing information from an inexact physics-based model, and from noisy sparse observations of reality. The multifidelity ensemble Kalman filter (MFEnKF) recently developed by the authors combines a full-order physical model and a hierarchy of reduced order surrogate models in order to increase the computational efficiency of data assimilation. The standard MFEnKF uses linear couplings between models, and is statistically optimal in case of Gaussian probability densities. This work extends the MFEnKF into to make use of a broader class of surrogate model such as those based on machine learning methods such as autoencoders non-linear couplings in between the model hierarchies. We identify the right-invertibility property for autoencoders as being a key predictor of success in the forecasting power of autoencoder-based reduced order models. We propose a methodology that allows us to construct reduced order surrogate models that are more accurate than the ones obtained via conventional linear methods. Numerical experiments with the canonical Lorenz'96 model illustrate that nonlinear surrogates perform better than linear projection-based ones in the context of multifidelity ensemble Kalman filtering. We additionality show a large-scale proof-of-concept result with the quasi-geostrophic equations, showing the competitiveness of the method with a traditional reduced order model-based MFEnKF.

97 MATHEMATICS AND COMPUTING↗

System Identification for Nonlinear Control Using Neural Networks

An approach to incorporating artificial neural networks in nonlinear, adaptive control systems is described. The controller contains three principal elements: a nonlinear inverse dynamic control law whose coefficients depend on a comprehensive model of the plant, a neural network that models system dynamics, and a state estimator whose outputs drive the control law and train the neural network. Attention is focused on the system identification task, which combines an extended Kalman filter with generalized spline function approximation. Continual learning is possible during normal operation, without taking the system off line for specialized training. Nonlinear inverse dynamic control requires smooth derivatives as well as function estimates, imposing stringent goals on the approximating technique.

Stengel, Robert F.↗

A system identification model for adaptive nonlinear control

A system identification model that combines generalized-spline function approximation with a nonlinear control system is described. The complete control system contains three main elements: a nonlinear-inverse-dynamic control law that depends on a comprehensive model of the plant, a state estimator whose outputs drive the control law, and a function approximation scheme that models the system dynamics. The system-identification task, which combines an extended Kalman filter with a function approximator modeled as an artificial neural network, is considered. The results of an application of the identification techniques to a nonlinear transport aircraft model are presented.

Linse, Dennis J.↗

Organized kinetic energy backscatter in the hurricane boundary layer from radar measurements

The fluid mechanics of hurricanes strongly depends on boundary layer energetics due to the warm-core nature of the system with peak velocities located at lower levels. One barrier that has inhibited a more complete characterization of energy transfer in the boundary layer is a lack of observations that resolve large, turbulent eddies. In particular, the occurrence and structure of upscale energy transfer (backscatter) in the hurricane boundary layer as well as the effects of backscatter on the vortex intensity are unknown. The analysis presented here of very high-resolution, three-dimensional wind observations from Hurricane Rita (2005) at peak intensity reveals large regions of organized backscatter in the boundary layer associated with coherent, turbulent eddies. Strong forwardscatter is also found next to the backscatter regions due to the interaction between adjacent eddies. Two components of the stress tensor are primarily responsible for this alternating scatter structure, as shown by large correlation coefficients between the fields: the radial–vertical component (τ13) and the azimuthal–vertical component (τ23) with average correlations of 79% and 49 %, respectively. The Leonard, Reynolds and cross-term stress components are also provided. The impact of the sub-filter-scale energy transfer is estimated by computing the kinetic energy budget for the resolved-scale and eddy-scale motions. The results show that the sub-filter-scale energy transfer term is of the same order as the other terms in the eddy-scale budgets, contributing between 16% and 40% to the local time tendency with an average contribution of approximately 30 %. These results indicate that the coherent turbulent eddies can affect the vortex dynamics through wave–wave nonlinear interactions, which can subsequently influence the wave–mean flow interactions. This is the first study to examine the full sub-filter-scale

Sydney Sroka↗

Scale filtering analysis of kinetic reconnection and its associated turbulence

Previously, using an incompressible von Kármán–Howarth formalism, the behavior of cross-scale energy transfer in magnetic reconnection and turbulence was found to be essentially identical to each other, independent of an external magnetic (guide) field, in the inertial and energy-containing ranges [Adhikari et al., Phys. Plasmas 30, 082904 (2023)]. However, this description did not account for the energy transfer in the dissipation range for kinetic plasmas. In this Letter, we adopt a scale-filtering approach to investigate this previously unaccounted-for energy transfer channel in reconnection. Using kinetic particle-in-cell simulations of antiparallel and component reconnection, we show that the pressure–strain interaction becomes important at scales smaller than the ion inertial length, where the nonlinear energy transfer term drops off. Also, the presence of a guide field makes a significant difference in the morphology of the scale-filtered energy transfer. These results are consistent with kinetic turbulence simulations, suggesting that the pressure strain interaction is the dominant energy transfer channel between electron scales and ion scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Stability analysis of Riccati covariance equations of Kalman filter.

The present paper takes the basic mathematical approach to analyze the stability of Riccati equations. First, a simple stability criterion like that of the linear constant coefficient system is sought for the nonlinear constant Riccati Equation. Then, a complete analysis on the limiting covariance P follows. The analysis is focussed on the main theorem. Finally, the computational aspects of the Riccati equations are analyzed with examples. The application of this analysis is to provide a simple stability criterion for the Kalman filter computation to test and predict filter convergence and thus modify filter parameters accordingly.

Teng, L.↗

Plasmonically assisted channels of photoemission from metals

We analyze recently measured nonlinear photoemission spectra from Ag surfaces that reveal resonances whose energies do not scale with the applied photon energy but stay pinned to multiples of bulk plasmon energy $\hbar$ω p above the Fermi level. To elucidate these unexpected and peculiar features we investigate the spectra of plasmons generated in a solid by the optically pumped electronic polarization and their effect on photoemission. By combining quadratic response formalism for calculations of photoemission yield, a nonperturbative approach to inelastic electron scattering, and first-principles calculations for the electronic structure, we demonstrate the dependence of probability amplitude for single- and multiplasmon excitations on the basic parameters characterizing the photon pulse and the system. The resulting multiexcitation spectrum evolves towards a truncated plasmonic coherent state. Analogous concept is extrapolated to interpret plasmon generation by multiphoton excited electronic polarization. Based on this we elaborate a scenario that the thus created real plasmons act as supplementary frequency-locked pump field for non-Einsteinian plasmonically assisted channels of photoemission from metals. The established paradigm enables assignment and assessment of the observed linear $\hbar$ω p and nonlinear 2$\hbar$ω p electron yields from Ag. Such effects may be exploited for selective filtering of optical energy conversion in electronic systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relatively new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance of staggered quadrature modulations over nonlinear satellite channels with uplink noise and intersymbol interference

In this paper, the performance of staggered quadrature modulations over nonlinear satellite channels is analyzed. The effects of uplink noise and intersymbol interference caused by transmitter filtering are included. The approach taken employs computational techniques based on moments of the interference. The expressions for the system bit error rate are derived for a general transponder model characterized by AM-AM and AM-PM conversion characteristics. Specific numerical results are presented for a hard-limited satellite repeater using staggered quadrature overlapped raised cosine (SQORC) and minimum-shift-keying (MSK) modulations.

Simon, M. K.↗

Optical calculation of correlation filters

A method is presented for designing optical correlation filters based on measuring intensity patterns in the Fourier plane. The method can be used in general to design any type of frequency plane filter but is especially attractive in the case of a binary phase only filter (BPOF). The method can produce a filter that is well matched to both the object, its transforming optical system and the spatial light modulator used in the correlator input plane. A working filter was produced using the technique, but the filter response was weak. The suspected causes of the weak output are imprecise Fourier plane positioning, nonlinearities in the recording process, and/or aliasing effects.

Knopp, Jerome↗

A Zonal Approach for Prediction of Jet Noise

A zonal approach for direct computation of sound generation and propagation from a supersonic jet is investigated. The present work splits the computational domain into a nonlinear, acoustic-source regime and a linear acoustic wave propagation regime. In the nonlinear regime, the unsteady flow is governed by the large-scale equations, which are the filtered compressible Navier-Stokes equations. In the linear acoustic regime, the sound wave propagation is described by the linearized Euler equations. Computational results are presented for a supersonic jet at M = 2. 1. It is demonstrated that no spurious modes are generated in the matching region and the computational expense is reduced substantially as opposed to fully large-scale simulation.

Shih, S. H.↗

Modeling the Dynamics of the Middle Atmosphere and Lower Thermosphere Under the Influence of Gravity Waves

Our Numerical Spectral Model (NSM), which extends from the ground up into the thermosphere, is non-linear, time-dependent and has been employed for 2D and 3D applications. The standard version of the NSM incorporates Hines' Doppler Spread Parameterization for small scale gravity waves (GW), but planetary waves generated in the troposphere have also been incorporated. The NSM has been applied to describe: (1) the anomalous seasonal variations of the zonal circulation and temperature in the upper mesosphere, (2) the equatorial oscillations (quasi-biennial and semi-annual oscillations (QBO and SAO)) extending from the stratosphere into the upper mesosphere, (3) the diurnal and semi-diurnal tides, and (4) the planetary waves that are excited in the mesosphere. With the emphasis to provide understanding, we present here results from numerical experiments with the NSM that shed light on the GW processes that are of central importance in the mesosphere and lower thermosphere. These are our conclusions: (1) The large semiannual variations in the diurnal tide (DT), with peak amplitudes observed around equinox, are produced primarily by GW interactions that involve, in part, planetary waves. The DT, like planetary waves, tends to be amplified by GW momentum deposition, which reduces also the vertical wavelength, but variations in eddy viscosity associated with GW interactions are also important. (2) The semidiurnal tide (SDT) and its phase in particular, is strongly influenced by the mean zonal circulation. The SDT, individually, is also amplified by GW. But the DT filters out GW such that the GW interaction effectively reduces the amplitude of the SDT, producing a strong nonlinear interaction between the DT and SDT. (3) Without external time dependent energy or momentum sources, planetary waves (PW) are generated in the model for zonal wavenumbers 1 to 4, which have amplitudes in the mesosphere above 50 km as large as 40 m/s and periods between 50 and 2 days. The waves are generated primarily during solstice conditions, which indicates that the baroclinic instability (associated with the GW induced reversal in the latitudinal temperature gradient) is playing an important role. Numerical experiment show that GW, directly, also greatly amplify the PW. A common feature of the PW generated in summer and winter is that their vertical wavelengths throughout the mesosphere are large, which indicates that the waves are not propagating freely but are generated throughout the region. Another common feature is that the PW propagate preferentially westward in summer and eastward in winter, being launched from the westward and eastward zonal winds that prevail respectively in summer and winter at altitudes below 80 km. (4) Planetary waves generated internally by baroclinic instability and GW interaction produce large amplitude modulations of the DT and SDT. In summary we conclude that GW play major roles in generating and amplifying the dynamical components in the MLT region and, acting principally through wave filtering, produce important non-linear interactions between the components.

Mayr, H. G.↗