A method for recursive subspace identification of continuous-time systems based on generalized Poisson moment functionals is proposed. Most of the existing subspace identification methods have concentrated mainly on t...
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A method for recursive subspace identification of continuous-time systems based on generalized Poisson moment functionals is proposed. Most of the existing subspace identification methods have concentrated mainly on the time-invariant discrete-time systems. The results of subspace identification methods are confined to the discrete-time cases, due to the difference on the construction of Hankel matrices. In addition, the time-invariant identification algorithms are not suitable for online identification cases. In order to solve the problems above, the time derivatives of Hankel matrices can be evaluated by generalized Poisson moment functionals, which provides a simple linear mapping for identification algorithm without the amplification of stochastic noises. The size of the data matrices is fixed a priori to fade the influence of old data to the updated data, which is a key to reduce computational burden and storage cost of recursive algorithms. The efficiency of the presented method is provided by comparing simulation results.
This paper discusses the infinite horizon static output feedback stochastic Nash games involving state-dependent noise in weakly coupled large-scale systems. In order to construct the strategy. the conditions for the ...
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This paper discusses the infinite horizon static output feedback stochastic Nash games involving state-dependent noise in weakly coupled large-scale systems. In order to construct the strategy. the conditions for the existence of equilibria have been derived front the solutions of the sets of cross-coupled stochastic algebraic Riccati equations (CSAREs). After establishing the asymptotic structure along with the positive semidefiniteness for the solutions of CSAREs, recursive algorithm for solving CSAREs is derived. As a result, it is shown that the proposed algorithm attains the reduced-order computations and the reduction of the CPU time. As another important contribution. the uniqueness of the strategy set is proved tor the sufficiently small parameter epsilon. Finally. in order to demonstrate the efficiency of the proposed algorithm, numerical example is given.
Minimizing the amount of communication required by a sensor network is crucial to minimizing both energy and time consumption, as well to operating covertly and robustly in communication-contested environments. This p...
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Minimizing the amount of communication required by a sensor network is crucial to minimizing both energy and time consumption, as well to operating covertly and robustly in communication-contested environments. This paper presents a novel intermittent communication control approach applicable to sensor networks deployed to sense and model spatio-temporal processes by nonparametric models such as Gaussian processes (GPs). The approach relies on a novel and efficient approximation of the GP average generalization error (AGE), as well as on novel GP sensor control and regression methods presented in this paper. This novel AGE approximation allows each sensor to characterize the nominal prediction performance of the learned GP model in the absence of communications. As a result, individual sensors can update the GP hyperparameters based solely on local measurements and decide to communicate only if and when their estimate of the nominal prediction performance falls below an acceptable threshold.
A recursive and efficient method for generating binary vectors in non-increasing order of their likelihood for a set of all binary vectors is proposed. Numerical results on experiments show the effectiveness of this m...
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A recursive and efficient method for generating binary vectors in non-increasing order of their likelihood for a set of all binary vectors is proposed. Numerical results on experiments show the effectiveness of this method. Efficient decoding algorithms with simulation results are also proposed as applications of the method.
Finite-control-set model predictive control (FCS-MPC) has many advantages in electric drive control systems but needs the accurate knowledge of the system parameters. The performance of the FCS-MPC will be deteriorate...
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Finite-control-set model predictive control (FCS-MPC) has many advantages in electric drive control systems but needs the accurate knowledge of the system parameters. The performance of the FCS-MPC will be deteriorated under parameter mismatches. This study proposes an adaptive FCS-MPC current control method for interior permanent magnet synchronous machine (IPMSM) drives subject to the inductance variations. The inductances are identified online by an adaptive observer with a recursive algorithm, which is inherently incorporated into the FCS-MPC control process to reduce the additional computational cost. Compensation methods are also proposed to improve the identification accuracy. The simulation and experimental results validate that, the IPMSM current control performance, speed-extension capability and drive efficiency are all improved by the proposed method.
We address the problem of minimax detecting and isolating abrupt changes in random signals. The criterion of optimality consists in minimizing the maximum mean detection/isolation delay for a given maximum probability...
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We address the problem of minimax detecting and isolating abrupt changes in random signals. The criterion of optimality consists in minimizing the maximum mean detection/isolation delay for a given maximum probability of false isolation and mean time before a false alarm. It seems that such a criterion has many practical applications especially for safety-critical applications, in monitoring dangerous industrial processes and also when the decision should be done in a hostile environment. The redundant strapdown inertial reference unit integrity monitoring problem is discussed. An asymptotic lower bound for the mean detection/isolation delay is given.
The paper is devoted to an integral equation algorithm for studying the scattering of plane waves by multilayer diffraction gratings under oblique incidence. The scattering problem is described by a system of Helmholt...
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The paper is devoted to an integral equation algorithm for studying the scattering of plane waves by multilayer diffraction gratings under oblique incidence. The scattering problem is described by a system of Helmholtz equations with piecewise constant coefficients in a"e(2) coupled by special transmission conditions at the interfaces between different layers. Boundary integral methods lead to a system of singular integral equations, containing at least two equations for each interface. To deal with an arbitrary number of material layers we present the extension of a recursive procedure developed by Maystre for normal incidence, which transforms the problem to a sequence of equations with 2x2 operator matrices on each interface. Necessary and sufficient conditions for the applicability of the algorithm are derived.
In this research, the issue of parameter estimation for control systems is considered to develop a highly efficient estimation approach for the purpose of satisfying the need of industrial process modelling. For dynam...
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In this research, the issue of parameter estimation for control systems is considered to develop a highly efficient estimation approach for the purpose of satisfying the need of industrial process modelling. For dynamical production processes, an error objective function in accordance with the dynamically sampled data is constructed for on-line identification. In order to simulate the instantaneous response of dynamical processes, the experimental scheme of impulse responses is adopted, and the observational data of impulse responses are used as the identification experimental data. In order to acquire high accuracy and stable performance, a hierarchical least mean square method is designed by means of the decomposition technique and the hierarchical principle. Finally, the superiority of the hierarchical least mean square approach is verified by the comparison simulation experiment and the effectiveness of the hierarchical least mean square method is proved by the detailed numerical examples.
This paper introduces wavelets and shows that they may be efficient and useful for the power distribution relaying. The wavelet transform of a signal consists in measuring the ''similarity'' between th...
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This paper introduces wavelets and shows that they may be efficient and useful for the power distribution relaying. The wavelet transform of a signal consists in measuring the ''similarity'' between the signal and a set of translated and scaled versions of ''mother wavelet''. The ''mother wavelet'' is a chosen fast decaying oscillation function. Wavelets are used to analyse transient earth fault signals in a 20 kV resonant grounded network as generated by EMTP. It is shown that wavelets may be employed for analysing records to study efficiently the faulted network. Moreover, this new technique can actually be implemented in real time for protection devices. Thus, it is suitable for application to protective relays.
By introducing a bivariate matrix-valued linear functional on the scalar polynomial space. a general two-dimensional (2-D) matrix Pade-type approximant (BMPTA) in the inner product space is defined in this paper. The ...
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By introducing a bivariate matrix-valued linear functional on the scalar polynomial space. a general two-dimensional (2-D) matrix Pade-type approximant (BMPTA) in the inner product space is defined in this paper. The coefficients of its denominator polynomials are determined by taking the direct inner product of matrices. The remainder formula is developed and an algorithm for the numerator polynomials is presented when the generating polynomials are given in advance. By means of the Hankel-like coefficient matrix, a determinantal expression of BMPTA is presented. Moreover, to avoid the computation of the determinants, two efficient recursive algorithms are proposed. At the end the method of BMPTA is applied to partial realization problems of 2-D linear systems. (C) 2009 Elsevier B.V. All rights reserved.
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