首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 612 毫秒
1.
Walsh product matrix is formed by the multiplication of Walsh vector and its transpose. The operation of Walsh product matrix on a coefficient vector equals the product of a coefficient matrix and a Walsh vector. This unique property of Walsh function is used to determine the unknown parameters of a general bilinear system from the input-output data. An example with satisfactory result is given.  相似文献   

2.
This paper discusses the identification problem for a class of nonlinear systems. A member of this class may be represented by a single-valued power-law type nonlinearity preceded and succeeded by linear dyadic invariant systems. Such an arrangement allows for a Voltera functional series representation. The identification problem is then concerned with the specification of the associated Voltera kernels.Two approaches are presented for dealing with this problem. Both approaches are, however, based on Walsh function techniques. The first approach relies on direct output measurements when the input is a Walsh function. This approach is suitable for a deterministic case. The second approach assumes ergodic processes for the input. Based on measurements drawn from an input-output dyadic correlation function, determination of the Voltera kernels is made.  相似文献   

3.
Identification of autoregressive models with exogenous input (ARX) is a classical problem in system identification. This article considers the errors-in-variables (EIV) ARX model identification problem, where input measurements are also corrupted with noise. The recently proposed Dynamic Iterative Principal Components Analysis (DIPCA) technique solves the EIV identification problem but is only applicable to white measurement errors. We propose a novel identification algorithm based on a modified DIPCA approach for identifying the EIV-ARX model for single-input, single-output (SISO) systems where the output measurements are corrupted with coloured noise consistent with the ARX model. Most of the existing methods assume important parameters like input-output orders, delay, or noise-variances to be known. This work’s novelty lies in the joint estimation of error variances, process order, delay, and model parameters. The central idea used to obtain all these parameters in a theoretically rigorous manner is based on transforming the lagged measurements using the appropriate error covariance matrix, which is obtained using estimated error variances and model parameters. Simulation studies on two systems are presented to demonstrate the efficacy of the proposed algorithm.  相似文献   

4.
This paper establishes a clear procedure for the variational problem solution via the Walsh functions.technique. First the Walsh functions are introduced and their properties briefly summarized. Then an operational matrix is derived for integration use. The variational problems are solved by means of the direct method using the Walsh series. An illustrative example and a practical application to a heat conduction problem are included.  相似文献   

5.
The operational properties of the integration and product of Chebyshev polynomials are used in the analysis of bilinear systems by the approximation of time functions by truncated Chebyshev series. The operational properties are also applied to determine the unknown parameters of a general bilinear system from the input-output data. Examples with excellent results are given.  相似文献   

6.
A matrix, called the “delay operational matrix”, is constructed from the Walsh matrix. This matrix, together with some matrices obtained from the delay operational matrix after performing right-shift operations, is used to solve multi-delay linear dynamic systems. A simple example is given to compare the actual solution and the solution obtained by the techniques of this paper.  相似文献   

7.
The Walsh operational matrix for performing integration and solving state equations is generalized to fractional calculus for investigating distributed systems. A new set of orthogonal functions is derived from Walsh functions. By using the new functions, the generalized Walsh operational matrices corresponding to √s, √(s2+ 1), e-s and e-√s etc. are established. Several distributed parameter problems are solved by the new approach.  相似文献   

8.
This paper considers the parameter and order estimation for multiple-input single-output nonlinear systems. Since the orders of the system are unknown, a high-dimensional identification model and a sparse parameter vector are established to include all the valid inputs and basic parameters. Applying the data filtering technique, the input-output data are filtered and the original identification model with autoregressive noise is changed into the identification model with white noise. Based on the compressed sensing recovery theory, a data filtering-based orthogonal matching pursuit algorithm is presented for estimating the system parameters and the orders. The presented method can obtain highly accurate estimates from a small number of measurements by finding the highest absolute inner product. The simulation results confirm that the proposed algorithm is effective for recovering the model of the multiple-input single-output Hammerstein finite impulse response systems.  相似文献   

9.
我国高新技术产业与其他产业关联效应的经验分析   总被引：1，自引：0，他引：1  
李新  王敏晰 《软科学》2009,23(9):21-24
结合投入产出分析理论和产业关联理论,运用投入产出模型,通过对我国2002年的投入产出表中2001～2005年数据重新整合,测算了直接消耗系数、感应度系数和影响力系数等一系列经济参数,定量分析了高新技术产业与国民经济其他部门间的关联效应,并对其关联效应进行归类和动态分析,研究结果揭示了高新技术产业与相关产业部门的关联效应以及波及程度的比例关系。  相似文献   

10.
The problems of identification, analysis and optimal control have been recently studied via orthogonal functions. The particular orthogonal functions used up to now are the Walsh, the block-pulse and the Laguerre functions. In this paper, the Chebyshev functions are introduced and solutions for the aforementioned problems are established. The algorithms proposed are analogous to those already derived for the Walsh, block-pulse and Laguerre functions. The Chebyshev series approach presented here appears to have certain advantages over other orthogonal series, and they may therefore be more suitable for the study of the problems of identification, analysis and optimal control.  相似文献   

11.
This paper investigates the multiple model adaptive control problem of affine systems with unknown parameters. Firstly, an adaptive controller with resettable parameters and an adaptive law with projection function are designed to ensure the asymptotic tracking for the reference system and the boundedness of parameters. Secondly, a transformation of system is given to enable a finite-time parameter estimator to calculate the uncertain parameters in the system matrix and the affine item simultaneously. Then, a novel performance index to describe the error between the controlled plant and the identification model is given to orchestrate switchings among identification models aiming to choose the best one. Next, the sufficient condition of the asymptotic convergence for the system error is given. Finally, all designs are evaluated in a hardware-in-the-loop simulation platform of an aero-engine control system and compared with three other methods, the effectiveness and superiority are verified.  相似文献   

12.
This paper considers the parameter identification problem of a bilinear state space system with colored noise based on its input-output representation. An input-output representation of a bilinear state-space system is derived for the parameter identification by eliminating the state variables in the model, and a recursive generalized extended least squares algorithm is presented for estimating the parameters of the obtained model. Furthermore, a three-stage recursive generalized extended least squares algorithm is proposed for reducing the computational cost. The validity of the proposed method is evaluated through a numerical example.  相似文献   

13.
This paper considers the identification problem of bilinear systems with measurement noise in the form of the moving average model. In particular, we present an interactive estimation algorithm for unmeasurable states and parameters based on the hierarchical identification principle. For unknown states, we formulate a novel bilinear state observer from input-output measurements using the Kalman filter. Then a bilinear state observer based multi-innovation extended stochastic gradient (BSO-MI-ESG) algorithm is proposed to estimate the unknown system parameters. A linear filter is utilized to improve the parameter estimation accuracy and a filtering based BSO-MI-ESG algorithm is presented using the data filtering technique. In the numerical example, we illustrate the effectiveness of the proposed identification methods.  相似文献   

14.
A new method is employed to identify the unknown parameters of a bilinear system. This method expands the system input and output by block pulse functions and reduces the original identification problem to an algebraic form. Furthermore, the dyad formed by block pulse functions and its integral are in diagonal forms, whereas the integration of the “triple-product” matrix can be reduced to the upper triangular form. Consequently, only very few calculations are required to find the solution for the algebraic equation. Two examples are given to show that the use of this method is considerably more economical in computation time than the use of Walsh function expansion.  相似文献   

15.
The method of identifying first order plus time delay transfer function model proposed for unstable systems by Ananth and Chidambaram [Closed loop identification to transfer function model for unstable systems, J. Franklin Inst. 336 (1999) 1055-1061] is modified to avoid the stability problems [Cheres, Parameter estimation of an unstable system with a PID controller in a closed loop configuration, J. Franklin Inst., 2005, accepted for publication] of the method. Two modifications are proposed. In the first modification of the method, the under-determined algebraic equations problem is converted into an optimization problem for calculation of the three parameters of the first order plus time delay (FOPTD) model. A simple method is given for the initial guess values of the model parameters. In the second approach, from the definition of Laplace transform of the output response, a third equation is formulated. The resulted three equations, in terms of the three parameters of the transfer function model, are then numerically solved. Simulation results are given for the second order plus time delay transfer function considered by Cheres 2005 [Parameter estimation of an unstable system with a PID controller in a closed loop configuration, J. Franklin Inst., 2005, accepted for publication]. The responses of the identified models with the same PID controllers are compared with that of the actual system. PID controllers are designed based on the identified models. The closed loop responses of the controllers on the original system are evaluated and compared. The present methods give better control performances.  相似文献   

16.
Takagi-Sugeno (T-S) fuzzy models can provide an effective representation of complex nonlinear systems with a series of linear input/output submodels in terms of fuzzy sets and fuzzy reasoning. In this paper, the T-S fuzzy model approach is extended to the stability analysis and controller design for nonlinear systems with time delays. An improved stability condition is proposed by introducing adjustable parameters into the Lyapunov-Krasovskii functional. Stabilization approach for fuzzy state feedback is also presented. Sufficient conditions for the existence of fuzzy feedback gain are derived through the numerical solution of a set of obtained linear matrix inequalities (LMIs). Compared with the existing methods in the literature, the proposed approach has less conservatism and both the sizes of delay and its derivative are involved in the criterion. The dynamical performance of the system can be adjusted by changing the adjustable parameters. Finally, two examples are given to show the effectiveness of the proposed approach.  相似文献   

17.
In this paper, identification of discrete-time power spectra of multi-input/multi-output (MIMO) systems in innovation models from output-only time-domain measurements is considered.A hybrid identification algorithm unifying mixed norm minimization with subspace estimation method is proposed. The proposed algorithm first estimates a covariance matrix from measurements. A significant dimension reduction is achieved in this step. Next, a regularized nuclear norm optimization problem is solved to enforce sparsity on the selection of most parsimonious model structure. A modification of the covariance estimates in the proposed algorithm generates yet another algorithm capable of handling data records with sequentially and intermittently missing values. The new and the modified identification algorithms are tested on a numerical study and a real-life application example concerned with the estimation of joint power spectral density (PSD) of parallel road tracks.  相似文献   

18.
This paper deals with the problem of model reference control for linear parameter varying (LPV) systems. The LPV systems under consideration depend on a set of parameters that are bounded and available online. The main contribution of this paper is to design an LPV model reference control scheme for LPV systems whose state-space matrices depend affinely on a set of time-varying parameters that are bounded and available online. The design problem is divided into two subproblems: the design of the coefficient matrices of the controller and the design of the gain of the state feedback controller for LPV systems. The singular value decomposition is used to obtain the coefficient matrices, while the linear matrix inequality methodology is used to obtain the parameter-dependent state feedback gain of the control scheme. A simple numerical example is used to illustrate the proposed design and a coupled-tank process example is used to demonstrate the usefulness and practicality of the proposed design. Simulation and experimental results indicate that the proposed scheme works well.  相似文献   

19.
This paper presents three identification methods for dual-rate sampled systems. The first method combines the stochastic gradient algorithm with the polynomial transformation technique, which can estimate the parameters of the identification model. The second method is the finite impulse response model based stochastic gradient algorithm, which can indirectly estimate the parameters of the dual-rate systems by using all the inputs and the available outputs. The third method is the missing output estimation model based stochastic gradient algorithm with a forgetting factor, which can directly estimate the parameters of the dual-rate systems by using all the inputs and all the outputs (include the estimated outputs). An example is provided to verify the effectiveness of the proposed methods.  相似文献   

20.
This paper studies parameter estimation for a class of linear, continuous, time-varying dynamic systems whose state-space model's matrices are affine combinations of static matrix coefficients and the aforementioned time-varying scalar parameters. It is assumed that the coefficient matrices are all known, that the state is mensurable, and that the parameters are bounded piecewise continuous functions of time. Estimation methods are developed from basic equations for a single parameter first, and later extended to multiple parameters.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号