Number Of Time Delays Research Articles

An efficient method for predicting wheel-rail forces in coupled nonlinear train-track-bridge system using artificial neural networks

Wheel-rail forces are an essential indicator for vehicle safety evaluation. The calculation of wheel-rail forces for the coupled nonlinear train-track-bridge system using the direct numerical integration method is time-consuming, hindering the timely safety and reliability assessment of train operations. In this paper, an efficient method based on the nonlinear autoregressive with exogenous input artificial neural network (NARX-ANN) was proposed to predict the nonlinear wheel-rail force of trains on bridges caused by track irregularity. Firstly, samples of track irregularity time history were randomly generated using the stochastic harmonic function method. The vertical and lateral wheel-rail forces of the coupled nonlinear train-track-bridge system were calculated by numerical integration. Secondly, the NARX-ANN model was established and trained with a small number of randomly selected wheel-rail force samples. Finally, the wheel-rail forces obtained by numerical integration were regarded as the ground truth to verify the prediction accuracy of the NARX-ANN model. The influence of training configuration, initial output, and the number of time delays on prediction accuracy was systematically analyzed. The results showed that the NARX-ANN model could accurately predict the time history of wheel-rail forces. In addition, its computational efficiency is 19.35 times higher than that of the numerical integration method. It is hoped that this study can guide the stochastic analysis of the train–track–bridge system.

Assessment of micro-vibrations effect on the quality of remote sensing satellites images

ABSTRACT Recently, there is a growing interest in analysing the degrading effect of satellite micro-vibrations due to the rapid growth in satellite technologies and the urgent need to precisely extract a huge amount of information from satellite images. Different kinds of micro-vibration have a notable effect on the quality of satellite images. The main objective of this paper is to demonstrate and analyse the effect of all types of micro-vibration on the quality of images acquired by high-resolution satellites. An algorithm to simulate micro-vibrations is proposed. A very high-resolution satellite image from the Pleiades-neo satellite is selected as an example to be used in addressing the degrading effects of micro-vibrations. In this paper, the modulation transfer function (MTF) is used as a major function to model the degradation that has been conducted. Also, several quality metrics are used to quantitatively assess the degradation. The key result of this paper is the significant effect of micro-vibrations on the quality of remote sensing satellite images which is attributed to the main influential parameters. These parameters like blur diameter, vibration displacement, number of Time Delay and Integration (TDI) stages of the camera, and the ratio of the integration time to the vibration period.

Data-driven optimal tracking control of discrete-time linear systems with multiple delays via the value iteration algorithm

In this paper, the optimal tracking problem for discrete-time linear systems with multiple delays is studied without system dynamics. It is known that the total state of a system without specific dynamic characteristics is hard to be measured, unless such a system is equipped with massive sensors, which, however, may lead to an increase in cost and complexity for analysing. To deal with this problem and avoid adverse effects caused by using system state information, a new data-driven value iteration (DDVI) algorithm is proposed by considering three factors: past control inputs, system outputs, and external reference trajectories. Before the algorithm is proposed, a transformation is made to the original system according to the characteristics of the time-delay system, so that the time-delay number can be reduced or become a delay-free system. A novel data-driven state equation is derived from the historical data of the three factors, and then, it is adopted to solve the optimal control of multi-delay systems. Further results show that the proposed DDVI algorithm is convergent and the tracking error is asymptotically stable. Finally, simulations are provided to show the effectiveness of the controller.

Mathematical Analysis of Line Intersection and Shortest Distance Algorithms

The time of arrival (TOA) trilateration is one of the representative location detection technologies (LDT) that determines the true location of a mobile station (MS) using a unique intersection point of three circles based on three radii corresponding to distances between MS and base stations (BSs) and center coordinates of BSs. Since the distance between MS and BS is estimated by using the number of time delays, three circles based on the estimated radii are generally increased and they may not meet at a single point, resulting in the location estimation error. In order to compensate this estimation error and to improve estimation performance, we present two advanced TOA trilateration localization algorithms with detail mathematical expressions. The considered algorithms are the shortest distance algorithm, which calculates an average of three interior intersection points among an entire six intersection points from three intersecting circles, and the line intersection algorithm, which calculates an intersection point of three lines connecting two intersection points of two circles among the three circles, as the estimated location of the MS. In this paper, we present both algorithms with detailed mathematical expressions. The computer simulation results are provided to compare the location estimation performance of both algorithms. In addition, in this paper, mathematical analysis is provided to indicate the relation between the line intersection algorithm and the shortest distance algorithm. In this analysis, we verify that line equations based on the intersection points obtained from the shortest distance algorithm are identical to those obtained from the line intersection algorithm.

A second-order statistics method for blind source separation in post-nonlinear mixtures

• Derivation of the conditions and the constraints on the Post-Nonlinear (PNL) model for Second-Order Statistics (SOS)-based separation. • Proposition of an SOS-based method for separation using a time-extended formulation. • Formulation considers the analytical computation of the time-extended covariance matrices. • Promising perspectives for the extension to any polynomial mixing functions in the PNL model. In the context of nonlinear Blind Source Separation (BSS), the Post-Nonlinear (PNL) model is of great importance due to its suitability for practical nonlinear problems. Under certain mild constraints on the model, Independent Component Analysis (ICA) methods are valid for performing source separation, but requires use of Higher-Order Statistics (HOS). Conversely, regarding the sole use of the Second-Order Statistics (SOS), their study is still in an initial stage. In that sense, in this work, the conditions and the constraints on the PNL model for SOS-based separation are investigated. The study encompasses a time-extended formulation of the PNL problem with the objective of extracting the temporal structure of the data in a more extensive manner, considering SOS-based methods for separation, including the proposition of a new one. Based on this, it is shown that, under some constraints on the nonlinearities and if a given number of time delays is considered, source separation can be successfully achieved, at least for polynomial nonlinearities. With the aid of metaheuristics called Differential Evolution and Clonal Selection Algorithm for optimization, the performances of the SOS-based methods are compared in a set of simulation scenarios, in which the proposed method shows to be a promising approach.

Delay-dependent stability analysis by using delay-independent integral evaluation

For the stability analysis of time-delay systems, the available methods usually require the exact evaluation of some quantities. The definite integral stability method, originated from the Argument Principle or the Cauchy Theorem, is effective because it only requires a rough estimation of the testing integral over a finite interval to judge stability. However, no general rule is given in the literature for properly choosing the upper limit of the testing integral. In this paper, two simple algorithms are presented for finding the parameter-dependent critical upper limit and a parameter-independent upper limit without any restriction on the number of time delays. These results improve and complete the definite integral stability method. As illustrated by the numerical examples, the proposed algorithms work effectively and accurately.

Line Intersection Algorithm for the Enhanced TOA Trilateration Technique

The location determination technology (LDT) is one of the core techniques for the location-based services (LBS) which has various applications, including a mobile robot, for the modern wireless communication system. The time of arrival (TOA), which is a kind of LDTs based on the cellular network, estimates the location of the specific user or object using a trilateration method based on the received signals from three base stations (BS). The true location of a mobile station (MS) is determined based on an intersection point of three circles with the radius corresponding to the distance between each BS to MS. Since the TOA method estimates the distance between BS and MS using the number of time delay, these three circles should not generally meet at a point and the performance of the location detection should be degraded in this case. In order to overcome this problem, we propose the mobile location detection algorithm based on a line intersection of the TOA geometry. In the case of those three circles do not meet at a point; in general, there are six intersection points and three lines which connect two intersection points. In this paper, we determine an intersection point of three lines as the location of a MS. The computer simulation example is provided to illustrate the location detection performance of the proposed algorithm.

Novel adaptive learning control of linear systems with completely unknown time delays

A novel output-feedback adaptive learning control approach is developed for a class of linear time-delay systems. Three kinds of uncertainties: time delays, number of time delays, and system parameters are all assumed to be completely unknown, which is different from the previous work. The design procedure includes two steps. First, according to the given periodic desired reference output and the allowed bound of tracking error, a suitable finite Fourier series expansion (FSE) is chosen as a practical reference output to be tracked. Second, by expressing the delayed practical reference output as a known time-varying vector multiplied by an unknown constant vector, we combine three kinds of uncertainties into an unknown constant vector and then estimate the vector by designing an adaptive law. By constructing a Lyapunov-Krasovskii functional, it is proved that the system output can asymptotically track the practical reference signal. An example is provided to illustrate the effectiveness of the control scheme developed in this paper.

Mars Reconnaissance Orbiter's High Resolution Imaging Science Experiment (HiRISE)

The HiRISE camera features a 0.5 m diameter primary mirror, 12 m effective focal length, and a focal plane system that can acquire images containing up to 28 Gb (gigabits) of data in as little as 6 seconds. HiRISE will provide detailed images (0.25 to 1.3 m/pixel) covering ∼1% of the Martian surface during the 2‐year Primary Science Phase (PSP) beginning November 2006. Most images will include color data covering 20% of the potential field of view. A top priority is to acquire ∼1000 stereo pairs and apply precision geometric corrections to enable topographic measurements to better than 25 cm vertical precision. We expect to return more than 12 Tb of HiRISE data during the 2‐year PSP, and use pixel binning, conversion from 14 to 8 bit values, and a lossless compression system to increase coverage. HiRISE images are acquired via 14 CCD detectors, each with 2 output channels, and with multiple choices for pixel binning and number of Time Delay and Integration lines. HiRISE will support Mars exploration by locating and characterizing past, present, and future landing sites, unsuccessful landing sites, and past and potentially future rover traverses. We will investigate cratering, volcanism, tectonism, hydrology, sedimentary processes, stratigraphy, aeolian processes, mass wasting, landscape evolution, seasonal processes, climate change, spectrophotometry, glacial and periglacial processes, polar geology, and regolith properties. An Internet Web site (HiWeb) will enable anyone in the world to suggest HiRISE targets on Mars and to easily locate, view, and download HiRISE data products.

Complete stability robustness of third-order LTI multiple time-delay systems

A unique procedure is presented in this paper, for a complete stability robustness of the third-order LTI multiple time-delay systems (LTI-MTDS). The uniqueness of the treatment is simply due to the fact that there is no comparable methodology, presently, in the literature. The end result of this procedure is an exhaustive and precise determination of the stable regions in the domain of time delays. The backbone of the method is a novel framework called “the cluster treatment of characteristic roots, (CTCR)”. CTCR is constructed over two fundamental propositions. The first proposition claims the existence of a bounded number of so-called “ kernel curves”, where the only imaginary characteristic roots occur. The second proposition is on an interesting directional invariance property of the crossing tendencies of these imaginary roots. For simplicity of conveyance and without loss of generality, the number of time delays is taken as two in this document. The new methodology is expandable to higher-order dynamics with more time delays than two, as the authors intend to demonstrate in future publications.

Fault detection and isolation by a continuous parity space method

The well-known parity space method for fault detection and isolation is generalized to a continuous-time case. As in the discrete-time case, it is shown that the parity space equations can be implemented using a number of time delays, and are equivalent to a continuous deadbeat observer. Algorithms for isolation of sensor and actuator faults are derived and illustrated by a numerical example.

Use of multiple time-delays as controllers in IMC schemes

Abstract Multiple time-delays with adjustable gains are proposed as controllers of IMC schemes. Such a controller is composed of a finite number of time-delays which are connected in parallel. Given a random disturbance with known power spectral density, gains of the time-delays are determined so as to minimize the output variance of the system. The optimization is performed by means of orthogonal projection in a finite-dimensional space. In the case of a plant with minimum-phase, the minimum variance can be made arbitrarily small by increasing the number of time-delays.