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Adaptive finite-time tracking control of 6DOF spacecraft motion with inertia parameter identification

IET CONTROL THEORY AND APPLICATIONS 2019年第13期13卷 2075-2085页

作者： Zhao, Qin Duan, Guangren Harbin Inst Technol Ctr Control Theory & Guidance Technol Harbin 150001 Heilongjiang Peoples R China Harbin Inst Technol State Key Lab Robot & Syst Harbin 150001 Heilongjiang Peoples R China

This study deals with the problem of relative motion control with 6 degrees of freedom (6DOF) for spacecrafts without a priori knowledge of the inertia parameters. Considering the system natural couplings, the integrated rotational and translational dynamics of the spacecraft are achieved. By a series of first-order filter operations, an expression of the parameter estimation error is derived and then used for the design of an integrated finite-time tracking controller applying adaptive backstepping technique. Proven by the Lyapunov theory, the proposed controller can guarantee that the errors of trajectory tracking and parameter identification simultaneously converge to zero in finite time. Furthermore, to be applied in practice, the controller is adapted for the spacecraft subject to external disturbance and input saturation. Compared with the previous control designs, the proposed control strategy can realise inertia parameter identification together with tracking of command position and attitude in finite time, in the presence of input saturation and external disturbance. The effectiveness of the control law is finally demonstrated by numerical simulations.

关键词： control nonlinearities adaptive control space vehicles Lyapunov methods attitude control parameter estimation control system synthesis motion control vehicle dynamics filtering theory trajectory control system natural couplings integrated rotational dynamics first-order filter operations parameter estimation error integrated finite-time tracking controller adaptive backstepping technique trajectory tracking finite time external disturbance input saturation control strategy inertia parameter identification control law 6DOF spacecraft motion relative motion control adaptive finite-time tracking control integrated translational dynamics Lyapunov theory command position tracking command attitude tracking

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A COMPARATIVE STUDY OF COMMUTING MATRIX APPROACHES FOR THE DISCRETE FRACTIONAL FOURIER TRANSFORM

A COMPARATIVE STUDY OF COMMUTING MATRIX APPROACHES FOR THE D...

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IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)

作者： Bhatta, Ishwor Santhanam, Balu Univ New Mexico Dept ECE Albuquerque NM 87131 USA

ISBN: (纸本)9781467391696

As an extension of the conventional Fourier transform and as a time-frequency signal analysis tool, the fractional Fourier transforms (FRFT) are suitable for dealing with various types of non-stationary signals. Computation of the discrete fractional Fourier transform (DFRFT) and its chirp concentration properties are both dependent on the basis of DFT eigenvectors used in the computation. Several DFT-eigenvector bases have been proposed for the computation of transform, and there is no common framework for comparing them. in this paper, we compare several different approaches from a conceptual viewpoint and review the differences between them. We discuss five different approaches to find centered-DFT (CDFT) commuting matrices and the various properties of these commuting matrices. We study the properties of the eigenvalues and eigenvectors of these commuting matrices to determine whether they resemble those of corresponding continuous Gauss-Hennite operator. We also measure the performance of these five approaches in terms of: mailobe-to-sidelobe ratio, 10-dB bandwidth, quality factor, linearity of eigenvalues, chirp parameter estimation error, and, finally the peak-to-parameter mapping regions. We compare the five approaches using these performance metrics and point out that the modified QMFD approach produces the best results in terms of bandwidth of the spectral peak for a chirp, invertibility of the peak parameter mapping, linearity of the eigenvalue spectrum and chirp parameter estimation errors.

关键词： Discrete fractional Fourier transform linear chirp signal chirp parameter estimation parameter estimation error peak-to-parameter mapping invertibilty region

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CORDIC DIFFERENTIAL MODEL OF CHARACTERISTIC FUNCTIONS OF 3D TERAGERTZ FMCW RADAR 24

<i>CORDIC</i> DIFFERENTIAL MODEL OF CHARACTERISTIC FUNCTIONS...

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24th International Crimean Conference Microwave & Telecommunication Technology (CriMiCo)

作者： Kosovets, M. Pavlov, O. SPE Quantor Kiev Ukraine Natl Tech Univ Ukraine KPI UA-03056 Kiev Ukraine

ISBN: (纸本)9789663354125

The equation of a differential model such as CORDIC is obtained and parameter estimations of FMCW radar at different noise levels are experimentally confirmed. Good results are obtained when the noise level is less than 60 dB, in case of a high noise level an estimation error increases, and at very high noise levels the result is not predictable and untrue.

关键词： CW radar FM radar radar signal processing 3D teragertz FMCW radar CORDIC differential model noise level parameter estimation error Educational institutions Electronic mail Mathematical model Noise level Radar Solid modeling Three-dimensional displays Noise levels frequency modulated radars three-dimensional displays Radar signal processing entity modeling electronic mail Educational institutions frequency-modulated-continuous-wave radar parameter estimation radar Eigenfunctions Mathematical Model

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Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models

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JOURNAL OF ECONOMETRICS 2011年第2期161卷 304-324页

作者： Corradi, Valentina Swanson, Norman R. Univ Warwick Dept Econ Coventry CV4 7AL W Midlands England Rutgers State Univ Dept Econ New Brunswick NJ 08901 USA

This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, we first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models. We then construct tests that are in the spirit of Diebold and Mariano (1995) and White (2000). In order to establish the asymptotic properties of our tests, we also develop a recursive variant of the nonparametric simulated maximum likelihood estimator of Fermanian and Salanie (2004). In an empirical illustration, the predictive densities from several models of the one-month federal funds rates are compared. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Block bootstrap Diffusion processes Jumps Nonparametric simulated quasi maximum likelihood parameter estimation error Recursive estimation Stochastic volatility

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Seeing Inside the Black Box: Using Diffusion Index Methodology to Construct Factor Proxies in Large Scale Macroeconomic Time Series Environments

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ECONOMETRIC REVIEWS 2010年第5-6期29卷 476-510页

作者： Armah, Nii Ayi Swanson, Norman R. Rutgers State Univ Dept Econ New Brunswick NJ 08901 USA Fed Reserve Bank Philadelphia Philadelphia PA USA

In economics, common factors are often assumed to underlie the co-movements of a set of macroeconomic variables. For this reason, many authors have used estimated factors in the construction of prediction models. In this article, we begin by surveying the extant literature on diffusion indexes. We then outline a number of approaches to the selection of factor proxies (observed variables that proxy unobserved estimated factors) using the statistics developed in Bai and Ng (2006a,b). Our approach to factor proxy selection is examined via a small Monte Carlo experiment, where evidence supporting our proposed methodology is presented, and via a large set of prediction experiments using the panel dataset of Stock and Watson (2005). One of our main empirical findings is that our osmoothedo approaches to factor proxy selection appear to yield predictions that are often superior not only to a benchmark factor model, but also to simple linear time series models which are generally difficult to beat in forecasting competitions. In some sense, by using our approach to predictive factor proxy selection, one is able to open up the oblack boxo often associated with factor analysis, and to identify actual variables that can serve as primitive building blocks for (prediction) models of a host of macroeconomic variables, and that can also serve as policy instruments, for example. Our findings suggest that important observable variables include various SP500 variables, including stock price indices and dividend series;a 1-year Treasury bond rate;various housing activity variables;industrial production;and exchange rates.

关键词： Diffusion index Factor Forecast Macroeconometrics parameter estimation error Proxy

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COST-UTILITY ANALYSIS OF BEHAVIORAL INTERVENTIONS FOR HIV-INFECTED PERSONS TO REDUCE HIV TRANSMISSION IN THE USA

COST-UTILITY ANALYSIS OF BEHAVIORAL INTERVENTIONS FOR HIV-IN...

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2010 Winter Simulation Conference

作者： Soorapanth, Sada Chick, Stephen E. San Francisco State Univ Dept Decis Sci 1600 Holloway Ave San Francisco CA 94132 USA INSEAD Technol & Operat Management Area F-77300 Fontainebleau France

ISBN: (纸本)9781424498642

We developed an ordinary differential equation model to analyze the cost and utility (measured in quality adjusted life years, or QALYs) of three published behavioral HIV interventions that aim to reduce the risk of transmission from HIV-infected persons to their sexual partners. The ODE model maps measurements of behavioral risk reduction parameters, estimated from sampling, into costs and QALYs. Monte Carlo sampling was used to perform a probabilistic sensitivity analysis to quantify uncertainty in costs and QALYs due to parameter estimation error from sampling. The results suggested that the behavioral interventions considered in this study are most likely to be cost-saving, or at least cost-effective. Our study shows how statistical estimates of behavioral measures translates into uncertainty about health costs and outcomes and suggests implications for which data are important to collect when assessing cost-utility tradeoffs, and not just measures of risk reduction from behavioral interventions.

关键词： HIV transmission HIV-infected persons Monte Carlo methods Monte Carlo sampling USA behavioral interventions cost-utility analysis differential equations diseases medical computing ordinary differential equation model parameter estimation error probabilist

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A simulation-based specification test for diffusion processes

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JOURNAL OF BUSINESS & ECONOMIC STATISTICS 2008年第2期26卷 176-193页

作者： Bhardwaj, Geetesh Corradi, Valentina Swanson, Norman R. Bates & White San Diego CA 92130 USA Univ Warwick Dept Econ Coventry CV4 7AL W Midlands England Rutgers State Univ Dept Econ New Brunswick NJ 08901 USA

This article makes two contributions. First, we outline a simple simulation-based framework for constructing conditional distributions for multifactor and multidimensional diffusion processes, for the case where the functional form of the conditional density is unknown. The distributions can be used, for example, to form predictive confidence intervals for time period t + tau, given information up to period t. Second, we use the simulation-based approach to construct a test for the correct specification of a diffusion process. The suggested test is in the spirit of the conditional Kolmogorov test of Andrews. However, in the present context the null conditional distribution is unknown and is replaced by its simulated counterpart. The limiting distribution of the test statistic is not nuisance parameter-free. In light of this, asymptotically valid critical values are obtained via appropriate use of the block bootstrap. The suggested test has power against a larger class of alternatives than tests that are constructed using marginal distributions/densities. The findings of a small Monte Carlo experiment underscore the good finite sample properties of the proposed test, and an empirical illustration underscores the ease with which the proposed simulation and testing methodology can be applied.

关键词： block bootstrap finance continuous time model parameter estimation error simulated GMM stochastic volatility

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Predictive density and conditional confidence interval accuracy tests

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JOURNAL OF ECONOMETRICS 2006年第1-2期135卷 187-228页

作者： Corradi, Valentina Swanson, Norman R. Queen Mary Univ London Dept Econ London E1 4NS England Rutgers State Univ Dept Econ New Brunswick NJ 08901 USA

This paper outlines testing procedures for assessing the relative out-of-sample predictive accuracy of multiple conditional distribution models. The tests that are discussed are based on either the comparison of entire conditional distributions or the comparison of predictive confidence intervals. We also briefly survey existing related methods in the area of predictive density evaluation, including methods based on the probability integral transform and the Kullback-Leibler Information Criterion. The procedures proposed in this paper are similar in many ways to [Andrews', 1997. A conditional Kolmogorov test. Econometrica 65, 1097-1128.] conditional Kolmogorov test and to [White's, 2000. A reality check for data snooping. Econometrica 68, 1097-1126.] reality check. In particular, a predictive density test is outlined that involves comparing square (approximation) errors associated with models i, i = 1,..., n, by constructing weighted averages over U of E((F(i)(u vertical bar Z(t), theta(dagger)(i)) - F(0)(u vertical bar Z(t), theta(0)))(2)), where F(0)((.)vertical bar(.)) and F(i)((.)vertical bar(.)) are true and model-i distributions, u E U, and U is a possibly unbounded set on the real line. A conditional confidence interval version of this test is also outlined, and appropriate bootstrap procedures for obtaining critical values when predictions used in the formation of the test statistics are obtained via rolling and recursive estimation schemes are developed. An empirical illustration comparing alternative predictive models for U.S. inflation is given for the predictive confidence interval test. (c) 2005 Elsevier B.V. All rights reserved.

关键词： block bootstrap rolling and recursive estimation scheme parameter estimation error predictive density

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Bootstrap conditional distribution tests in the presence of dynamic misspecification

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JOURNAL OF ECONOMETRICS 2006年第2期133卷 779-806页

作者： Corradi, Valentina Swanson, Norman R. Queen Mary Univ London Dept Econ London E1 4NS England Rutgers State Univ Dept Econ New Brunswick NJ 08901 USA

In this paper, we show the first order validity of the block bootstrap for Kolmogorov-type conditional distribution tests under dynamic misspecification and parameter estimation error. Our approach is unique because we construct statistics that allow for dynamic misspecification under both hypotheses. We consider two tests;the CK test of Andrews [1997. A conditional Kolmogorov test, Econometrica 65, 1097-1128], and a version of the DGT test of Diebold, Gunther and Tay [1998a. Evaluating density forecasts with applications to finance and management. International Economic Review 39, 863-883]. Test limiting distributions are Gaussian processes with covariance kernels that reflect dynamic misspecification and parameter estimation error. Critical values are based on an extension of the empirical process version of the block bootstrap to the case of nonvanishing parameter estimation error. Monte Carlo experiments are also carried out. (c) 2005 Elsevier B.V. All rights reserved.

关键词： block bootstrap conditional distributions conditional Kolmogorov tests dynamic misspecification parameter estimation error

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An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series

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JOURNAL OF ECONOMETRICS 2006年第1-2期131卷 539-578页

作者： Bhardwj, G Swanson, NR Rutgers State Univ Dept Econ New Brunswick NJ 08901 USA

This paper addresses the notion that many fractional I(d) processes may fall into the "empty box" category, as discussed in Granger (Aspects of research strategies for time series analysis, Presentation to the Conference oil New Developments in Time Series Economics, Yale University, 1999). We present ex ante forecasting evidence which suggests that ARFIMA models estimated using a variety of standard estimation procedures yield "approximations" to the true unknown underlying DGPs that sometimes provide significantly better out-of-sample predictions than AR, MA, ARMA, GARCH, and related models, based on analysis of point mean-square forecast errors (MSFEs), and based on the use of predictive accuracy tests. The strongest evidence in favor of ARFIMA models arises when various transformations of 5 major stock index returns are examined. Additional evidence based on analysis of the Stock and Watson (J. Bus. Econom. Stat. 20 (2002) 147-162) data set, the returns series data set examined by Ding et al. (J. Empirical Finance 1 (1993) 83-106). and based on a series of Monte Carlo experiments is also discussed. (c) 2005 Elsevier B.V. All rights reserved.

关键词： fractional integration long memory parameter estimation error stock returns long horizon prediction

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