Nonperiodic Sampling Research Articles

An inverse method for characterization of dynamic response of 2D structures under stochastic conditions

The reliable estimation of the wavenumber space (k-space) of the plates remains a long-term concern for acoustic modeling and structural dynamic behavior characterization. Most current analyses of wavenumber identification methods are based on the deterministic hypothesis. To this end, an inverse method is proposed for identifying wave propagation characteristics of two-dimensional structures under stochastic conditions, such as wavenumber space, dispersion curves, and band gaps. The proposed method is developed based on an algebraic identification scheme in the polar coordinate system framework, thus named Algebraic K-Space Identification (AKSI) technique. Additionally, a model order estimation strategy and a wavenumber filter are proposed to ensure that AKSI is successfully applied. The main benefit of AKSI is that it is a reliable and fast method under four stochastic conditions: (A) High level of signal noise; (B) Small perturbation caused by uncertainties in measurement points’ coordinates; (C) Non-periodic sampling; (D) Unknown structural periodicity. To validate the proposed method, we numerically benchmark AKSI and three other inverse methods to extract dispersion curves on three plates under stochastic conditions. One experiment is then performed on an isotropic steel plate. These investigations demonstrate that AKSI is a good in-situ k-space estimator under stochastic conditions.

Neural learning-based dual channel event-triggered deployment control of space tethered system with intermittent output

In this paper, we investigate the dual-channel event-triggered deployment control for the space tethered system with intermittent output. Two different dynamic event-triggered mechanisms are designed to implement the event-based state sampling and the event-based input sampling, in which the data transmission frequencies are reduced at the dual channel, namely sensor-to-controller and controller-to-actuator. Then, the neural network (NN) state observer based on the intermittent output is designed to estimate the unmeasurable state under external disturbance, and the observer-based sliding mode controller is designed. Furthermore, because of the non-periodic sampling of the state signal and the output signal, the closed-loop system is proved via the analysis of the hybrid system, and the Zeno behavior is avoidance under these two event-triggered conditions. Finally, the simulation tests are implemented to verify the effectiveness of the proposed scheme.

Wavenumber identification of 1D complex structures using Algebraic Wavenumber Identification (AWI) technique under complex conditions

The dynamic characterization of complex structures raises the need for a robust experiment-based wavenumber identification method, especially when they are tested under complex conditions. To this end, this paper presents an optimized Algebraic Wavenumber Identification (AWI) method and describes the dynamic behavior of three complex structures under a series of complex conditions through AWI. The first novelty of this paper is to optimize AWI in terms of computation efficiency and accuracy by two solutions: (a) the multiple integral of AWI, which acts as a filter, is explicitly solved by the least squares fitting method, significantly reducing the computation cost, especially when multiple samples are used as input parameters; (b) a sampling strategy is provided to further improve the robustness of the AWI to measurement errors. On this basis, an AWI implementation procedure is proposed for experimental tests under complex conditions. The second novelty of this paper is on the applications of AWI in wave propagation parameters identification of complex structures, including the damping loss factor estimation of a viscoelastic beam and a honeycomb sandwich beam, the band gap identification of a meta-structure, and experimental dispersion curves extraction of these three complex structures. The third novelty of this paper is the experimental validation of AWI under a series of complex conditions, including signal noise, non-periodic sampling, and uncertainty of measuring points’ geometric coordinates. The experimental and numerical results have been compared to two popular inverse methods, namely, Inhomogeneous Wave Correlation (IWC) and INverse COnvolution MEthod (INCOME), demonstrating the validity of the AWI implementation procedure proposed in this paper.

Hierarchical Event-Triggered MPC-Based Coordinated Control for HVRT and Voltage Restoration of Large-Scale Wind Farm

This paper proposes a hierarchical event-triggered model predictive control (HEMPC)-based voltage control strategy to coordinate the reactive power (Var) outputs among all WTs for improving the high-voltage ride-through (HVRT) and post-fault voltage restoration capability of the large-scale wind farms (WFs), while reducing the heavy computational task of the WF controller. The event-triggering condition and optimal controller are designed to activate the proposed HEMPC strategy based on the system state deviation and input-to-state stability (ISS) mechanism, which can substantially decrease data communication in a non-periodic sampling fashion. A hierarchical solution method based on the alternating direction method of multipliers (ADMM) is developed, aiming to further improve the computing efficiency of the voltage optimization problem of the large-scale WF. Two time-domain WF simulation cases in Matlab/Simulink corroborate that the proposed HEMPC strategy is more efficient in minimizing the WT terminal voltage deviations and reducing the computational burdens of the WF controller compared with traditional control strategies.

An architecture to implement generalized sampling in Online Laboratories

This work describes an extension of RIP (Remote Interoperability Protocol) to cope with generalized sampling (i.e. combine different methods of sampling for a set of variables/states) in online laboratories (OL). We discuss, from the OL perspective, some alternative approaches to non-periodic sampling, analyze some ad-hoc solutions that have been successfully used in the past, and then we create a model with three different levels of abstraction model that captures the relevant aspects of the sampling that appear in online labs. Then, we propose an extension of RIP that support the proposed abstract model. Finally we present two examples of implementation based on the proposed architecture.

Asynchronous Feedback Control for Delayed Fuzzy Degenerate Jump Systems Under Observer-Based Event-Driven Characteristic

This article is concerned with the issue of asynchronous feedback control for fuzzy degenerate jump systems with mode-dependent time-varying delays via Takagi–Sugeno fuzzy control technique under observer-based event-driven characteristic. The improved observer and event trigger transmit not only state estimate signals but also the information of Markovian jump modes to the controller under the networked nonperiodic sampling scheme. Applying parallel distributed compensation technique, the asynchronous fuzzy feedback controller is devised, and the asynchronous fuzzy controller modes are depicted by a hidden Markovian model, where the modes of fuzzy controller run asynchronously with that of the original degenerate fuzzy jump systems. Exponentially decreasing function is employed to devise the triggering threshold, which can ensure not only the admissibility of the delayed fuzzy degenerate jump systems but also the effectiveness of event-driven strategy. Original stochastic admissibility and asynchronous feedback control conditions are characterized by linear matrix inequalities. A numerical example and a single-link robot arm model are applied to illustrate the correctness and validity of the proposed observer-based event-driven asynchronous fuzzy feedback control technique.

Implementation and Performance Analysis of True Random Number Generator on FPGA Environment by Using Non-periodic Chaotic Signals Obtained from Chaotic Maps

In this study, FPGA implementation of a hybrid random number generator (HRNG) based on digital design techniques is given. The ring oscillators (ROs) are used as the noise source of HRNG, and true randomness is obtained by sampling jitter signals forming on the oscillators. The statistical quality and reliability of random number generators that used jitter as source of true randomness alone are often cryptographically insufficient. For this reason, one-dimensional discrete-time chaotic maps such as quadratic map, logistic map and Bernoulli shift map are benefited in order for HRNG to meet these cryptographic requirements. In contrast to many studies in the literature, non-periodic signals derived from chaotic systems of a powerful source of entropy are used instead of periodic signals for the sampling of jitter signals in the system. Depending on the usage of chaotic systems, output bit rate and reliability of high generator model that does not need post-processing techniques and is easily applicable to digital devices are obtained. The hybrid system is tested in total six different scenarios for two separate ring oscillator (RO) architectures of 25 and 114 pieces consisting of three different chaotic maps and equal-length inverters. The statistical qualifications of the random numbers obtained from HRNG for each scenario are verified by NIST 800-22 tests. Also, for each scenario, the design parameters of the generator are examined and the hardware performances and non-periodicity analyses of the chaotic maps are performed. Based on the obtained results, it is demonstrated that the HRNG based on non-periodic sampling can be used for cryptographic purposes.

Improving the resolution of an optical microscope using ring-like illumination and scanning the direction of the diffracted light with a slit

A non-periodic sample, which also contains a periodic structure with a period smaller than the resolution limit of the optical microscope used for imaging it, was illuminated with the cone of white-light produced by a ring-shaped condenser with a numerical aperture larger than the objective lens. By rotating a slit placed at the back focal plane of the objective lens, we obtained several pairs of real plane and Fourier plane images corresponding to different diffraction directions. We simulated, discussed, and demonstrated a numerical algorithm capable of producing a high-resolution image of the sample after processing the experimental images.

Rendimiento de Enfoques de Control Auto-Disparado


 
 
 El control auto-disparado produce secuencias de muestreo no periódico que varían dependiendo de factores de diseño relacionados con la estabilidad y el rendimiento del sistema a ser controlado. Dentro de este marco, recientemente han sido desarrollados dos enfoques dirigidos a minimizar un costo cuadrático, considerando un rendimiento óptimo y persiguiendo el mismo objetivo de control; cada una de ellos sigue una regla de muestreo diferente. Un enfoque se basa en mantener el valor de control actual tanto tiempo como sea posible, mientras que un umbral de rendimiento óptimo no se traspase. El otro enfoque se basa en la generación de una señal de control a trozos que se aproxima a una señal de control óptima continua, sujeta a determinadas limitaciones. Este artículo presenta un estudio comparativo entre los dos enfoques, proporcionando una percepción útil para la realización de futuras investigaciones. Como métricas de interés, el rendimiento de control y la utilización de recursos fueron considerados, y para evaluarlos, se hizo uso del intervalo de muestreo promedio y del costo normalizado. Se demostró que el diferente espacio de búsqueda de cada enfoque plantea un desafío para diseñar un marco de comparación equitativo, y que ambos enfoques superan al muestreo periódico. 
 
 

Consensus for heterogeneous multi-agent systems under fixed and switching topologies

The consensus problem for heterogeneous multi-agent systems under directed topologies is investigated. For continuous-time systems, a novel consensus algorithm is proposed. Based on a system transformation method, the consensus problem for heterogeneous multi-agent systems is converted into a consensus problem for homogeneous multi-agent systems. Necessary and sufficient conditions are presented to guarantee that the designed consensus algorithm asymptotically solves the consensus for heterogeneous multi-agent systems under a fixed topology. The final convergence states are shown explicitly for this case. Sufficient conditions are given to guarantee that heterogeneous multi-agent systems reach consensus asymptotically under switching topologies. The obtained results are superior obviously to the existing ones in the literature. The counterparts about discrete-time systems are also investigated. Both periodic sampling and nonperiodic sampling are considered. Numerical simulations are provided to illustrate the effectiveness of the obtained theoretical results.

The correlation of single-particle diffraction patterns as a continuous function of particle orientation.

A statistical model for X-ray scattering of a non-periodic sample to high angles is introduced. It is used to calculate analytically the correlation of distinct diffraction measurements of a particle as a continuous function of particle orientation. Diffraction measurements with shot-noise are also considered. This theory provides a general framework for a deeper understanding of single particle imaging techniques used at X-ray free-electron lasers. Many of these techniques use correlations as a measure of diffraction-pattern similarity in order to determine properties of the sample, such as particle orientation.

Calculation of Far-Field Radiation Pattern Using Nonuniformly Spaced Antennas by a Least Square Method

The far field pattern from a nonuniformly spaced antenna array is computed using a least squares method. The method originally developed for spectral estimation for a nonuniformly spaced finite data set is applied for the analysis of the far field pattern from unevenly spaced antennas, as the far field pattern is due to the spectrum of the location of the antenna elements. The advantage of using a nonuniformly sampled data is that it is not necessary to satisfy the Nyquist sampling criterion as long as the average value of the sampling rate is less than the Nyquist rate. For a Fourier-based technique which also computes a least squares solution for the spectrum using a periodic data set, the finite data set then has to be periodically repeated resulting in bias in the solution. The methodology presented in the paper does not assume a periodic extension of the data set and can discern between the positive and negative frequencies of the spectrum unlike in the well-known Lomb periodogram. Finally, by exploiting a Hilbert transform relationship between the coefficients of the parameters in the least squares formulation an approximate fast way to compute the spectrum from unevenly spaced finite-sized non-periodic samples of the data can be realized. The example presented in this paper deals with a one-dimensional array even though this methodology is general in nature and can easily be extended to the two-dimensional case.

Phased Array Bandwidth Enhancement Using a Novel Sampling Scheme

Phased arrays are a form of steerable antenna whose architecture makes the system complex and generally expensive. Their versatility and performance motivates the development of alternative structures which allow us to obtain simplified designs as powerful as the original approach but significantly cheaper. In this paper, a novel technique which collects information only from one antenna during each radio frequency cycle but introduces a restriction in the working bandwidth has been proposed. By studying the effect of the sampling order and optimizing it using backtracking or a genetic algorithm, the bandwidth is increased up to almost four times the original value for small arrays, and up to 25% of the carrier frequency for large arrays using maximum delay sorting. Finally, effectiveness of nonperiodic sampling order, which converts interfering harmonics into distributed background noise, is also shown.

State and event estimation for regime-switching systems under irregular and random sampling schemes

Estimation of states and events in randomly switching systems is studied under irregular and random sampling schemes. Probabilistic characterization of observability is presented under various sampling schemes and regime-switching processes. The characterization is derived on the basis of our recent results on sampling complexity for system observability. Observer design and algorithms are developed. 1. Introduction. This paper investigates estimation of states and events in ran- domly switching systems under various sampling schemes. The problems are typically studied under the names of regime-switching systems, hybrid systems, discrete-event systems, etc. Typically, such systems involve communication channels whose power and bandwidth limitations make it desirable to reduce resource consumption in sam- pling and quantization. It was shown in (29, 30) that traditional periodic sampling is inefficient in utility of such resources. More efficient sampling/quantiz ation schemes introduced in (29, 30) lead naturally to irregular sampling (also known as non-uniform or non-periodic sampling). Irregular and random sampling may occur also due to event triggered sampling (3, 22) or communication uncertainty and interruptions (9). When a system switches its dynamics, it introduces an event which is itself a dy- namic process whose state space is a finite set and its state also needs to be estimated. State estimation of linear dynamic systems is a traditional topic that has been well studied (14). Independently, observability of events has been studied extensively in discrete event systems (15, 18). References (25, 26) contain more recent studies on observability of sampled systems. Joint identification of states and events has been studied in hybrid systems (20, 25). Studies on fundamental properties of non-uniform sampling remain an active area of research, see (6) and the references therein for some recent work in this area. Some related results on identification, state estimation, and fault detection using binary or quantized outputs can be found in (13, 26, 31, 32, 35). This paper studies some fundamental issues in joint estimation of states and events when the events are stochastic processes. The main issues are: What are the conditions for observability? How many sampling points are needed to ensure

Design method to enhance the transmittance of a structured lens based on nonperiodic sampling

On the basis of the work of Chen, Zhou, Luo, and Du [Opt. Lett. 33, 753-755 (2008)], we propose a new method using nonperiodic sampling to design a high-transmittance structured lens. The sizes of the holes are decided by the phase requirements, and the holes are arranged with a fixed interval in the vertical direction while a variable interval in the horizontal direction. With this design method, holes can be arranged more compactly and the fill factor of the holes can be increased effectively. Numerical simulation is performed through the finite-difference time-domain method, and the results indicate that the transmittance of the lens climbs to 73.6%, which reaches almost 3.5 times that achieved in the above-mentioned work. Meanwhile, the simulated focal length agrees well with the theoretical design result with the error of 1.1% and the full width at half maximum of the focal spot is obtained similar to 1.16 times of the diffraction limit. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3528539]

Efficient Reconstruction Algorithms Using Shifted Lattices

In this paper, we consider sampling theory for irregular sampling sets of minimal density which are structured. An efficient method for the reconstruction of band-limited discrete signals from sampling sets which are unions of shifted lattices is developed. These sets are not necessarily periodic. A signal can be reconstructed from its samples provided the sampling set and the spectrum of the signal satisfy certain compatibility conditions. While explicit reconstruction formulas for unions of sampling lattices are possible, it is more convenient to use a recursive algorithm. A numerical example utilizing nonperiodic sampling sets implemented in MATLAB is given. The theory and the related algorithm has been applied to speech and image processing examples.

Photoactive periodic media

Photoactive (photochromic) multilayers of MoO3/SiO2 are studied optically before and after UV excitation. Enhancement in photochromic activity is observed over a wide spectrum and in particular near the photonic band edges where optical changes are up to 25 times greater than in similarly prepared bulk, nonperiodic samples. Applications to light-sensitive devices are discussed.

A Multisensor Deconvolution Problem

Meisters and Peterson gave an equivalent condition under which the multisensor deconvolution problem has a solution when there are two convolvers, each the characteristic function of an interval. In this article we find additional conditions under which the deconvolution problem for multiple characteristic functions is solvable. We extend the result to the space of Gevrey distributions and prove that every linear operator S, fromthe space of Gevrey functions with compact support onto itself, which commutes with translations can be represented as convolution with a unique Gevrey distribution T of compact support. Finally, we find explicit formula for deconvolvers when the convolvers satisfy weaker conditions than the equivalence conditions using nonperiodic sampling method.

Solving non-periodic structures using direct methods: phasing diffuse scattering.

The problem of reconstructing the charge density of a non-periodic sample from its diffuse X-ray scattering is considered. For a sample known to be isolated, an artificial superlattice may be assumed and the numerical direct methods of crystallography applied to the continuous distribution of diffuse scattering in order to solve the phase problem. This method is applied to simulated soft-X-ray transmission speckle patterns from a two-dimensional array of gold balls of 50 nm diameter. The results are relevant to efforts to phase the scattering from many individual macromolecules that cannot be crystallized, and to the scattering from individual inorganic nanoparticles.

Study of the influence of higher-order Laue zones on the exit wavefunction

Based on an analytical expression of electron dynamical diffraction derived recently, the exit wavefunctions of nonperiodic samples have been calculated. The results have shown that the amplitude and phase obtained by the analytical expression were in good agreement with those obtained using the multi-slice method. Besides, the influence of the higher-order Laue zone on the wavefunction for different sample thickness was studied in detail and the results showed that the exit wavefunction is dominated by the zero-order Laue zone. When the sample is very thin, the influence of the higher-order Laue zone should be considered.