共查询到20条相似文献,搜索用时 15 毫秒
1.
This paper presents a methodology for system identification of continuous-time state-space models from finite sampled input-output signals. The estimation problem of the consecutive time-derivatives and integrals of the input-output signals is considered. The appropriate frequency characteristcs of a linear filtering based on the Poisson moment functionals in regards to the derivative or integral estimation problem is shown. The proposed method combines therefore the Poisson moment functionals technique with subspace based state-space system identification methods. The developed algorithm is based on a generalized singular value decomposition to compensate the noise colouring caused by the linear prefiltering of the input-output data. Rules of thumb are presented to choose the design parameters and new regards to the selection of the Poisson filter cut-off frequency are introduced. Finally, the proposed method is applied to a multivariable winding processes. The experimental results emphasize the applicability of the developed methodology. 相似文献
2.
This paper studies the asymptotic behavior of nonparametric and parametric frequency domain identification methods to model linear dynamic systems in the presence of nonlinear distortions under some general conditions for random multisine excitations. In the first part, a related linear dynamic system (RLDS) approximation to the nonlinear system (NLS) is defined, and it is shown that the differences between the NLS and the RLDS can be modeled as stochastic variables with known properties. In the second part a parametric model for the RLDS is identified. Convergence in probability of this model to the RLDS is proven. A function of dependency is defined to detect and separate the presence of unmodeled dynamics and nonlinear distortions and to bound the bias error on the transfer function estimate 相似文献
3.
Csébfalvi B 《IEEE transactions on visualization and computer graphics》2008,14(2):289-301
In this paper prefiltered reconstruction techniques are evaluated for volume-rendering applications. All the analyzed methods perform a discrete prefiltering as a preprocessing of the input samples in order to improve the quality of the continuous reconstruction afterwards. Various prefiltering schemes have been proposed to fulfill either spatial-domain or frequency domain criteria. According to our best knowledge, however, their thorough comparative study has not been published yet. Therefore we derive the frequency responses of the different prefilteredreconstruction techniques to analyze their global behavior such as aliasing or smoothing. Furthermore, we introduce a novel mathematical basis to compare also their spatial-domain behavior in terms of the asymptotic local error effect. For the sake of fair comparison, we use the same linear and cubic B-splines as basis functions but combined with different discrete prefilters. Our goal with this analysis is to help the potential users to select the optimal prefiltering scheme for their specific applications. 相似文献
4.
永磁同步电机(PMSM)是一个非线性、多变量、强耦合系统,具有不确定的外部干扰;为了提高对其转速控制精度,采用改进自抗扰控制代替传统自抗扰控制(ADRC);通过插值法构建一个新的函数来代替ADRC中原有的最优控制函数,并用线性误差反馈控制率代替非线性误差反馈控制率(NLSEF)以此来降低调参难度;同时建立基于脉振高频注入法和滑模观测器法的位置辨识系统,以满足PMSM转子位置的辨识精度要求;仿真结果表明,改进ADRC能够在无位置传感器控制方法中取得较好的控制效果,转子位置估计的误差小于0.002 rad,转速估计误差小于0.02 rad/min,转速超调量小于4%,最大振荡不超过60 rad/min,与传统ADRC控制器相比系统抗扰动性更强,电机位置和速度辨识效果也更优。 相似文献
5.
This paper considers the measurement and the identification of nonlinear time-invariant single-input/single-output (SISO) systems, consisting of a multivariable linear dynamic system and one static nonlinear SISO system. This includes Wiener-Hammerstein systems in a linear feedback loop. The nonparametric identification of the frequency response functions of the linear parts are obtained without measuring the signals over the static nonlinearity. Measurements on an electronic circuit demonstrate the usability of this identification scheme 相似文献
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7.
A linear algorithm and a nonlinear algorithm for the problem of system identification in H ∞ posed by Helmicki et al. (1990) for discrete-time systems are presented. The authors derive some error bounds for the linear algorithm which indicate that it is not robustly convergent. However, the worst-case identification error is shown to grow as log(n ), where n is the model order. A robustly convergent nonlinear algorithm is derived, and bounds on the worst-case identification error (in the H ∞ norm) are obtained 相似文献
8.
基于非线性频谱数据驱动的动态系统故障诊断方法 总被引:1,自引:0,他引:1
基于非线性频谱数据驱动方法, 研究了动态系统的故障诊断问题. 利用一维非线性输出频率响应函数提出一种非线性频谱特征提取方法, 为了提高实时性, 采用变步长自适应辨识算法进行求解; 根据估计偏差实时地改变步长, 兼顾了收敛速度与稳态误差; 获取了非线性频谱特征之后, 利用最小二乘支持向量机分类器进行故障识别. 通过对提升设备的故障诊断问题进行实验研究, 所得结果表明, 所提出的算法识别率高, 能满足在线诊断要求. 相似文献
9.
S. Khadraoui M.N. Nounou A. Datta S.P. Bhattacharyya 《International journal of control》2013,86(9):1586-1596
The objective of this paper is to present a measurement-based control-design approach for single-input single-output linear systems with guaranteed bounded error. A wide range of control-design approaches available in the literature are based on parametric models. These models can be obtained analytically using physical laws or via system identification using a set of measured data. However, due to the complex properties of real systems, an identified model is only an approximation of the plant based on simplifying assumptions. Thus, the controller designed based on a simplified model can seriously degrade the closed-loop performance of the system. In this paper, an alternative approach is proposed to develop fixed-order controllers based on measured data without the need for model identification. The proposed control technique is based on computing a suitable set of fixed-order controller parameters for which the closed-loop frequency response fits a desired frequency response that meets the desired closed-loop performance specifications. The control-design problem is formulated as a nonlinear programming problem using the concept of bounded error. The main advantages of our proposed approach are: (1) it guarantees that the error between the computed and the desired frequency responses is less than a small value; (2) the difficulty of finding the globally optimal solution in the error minimisation problem is avoided; (3) the controller can be designed without the use of any analytical model to avoid errors associated with the identification process; and (4) low-order controllers can be designed by selecting a fixed low-order controller structure. To experimentally validate and illustrate the efficacy of the proposed approach, proportional-integral measurement-based controllers are designed for a DC (direct current) servomotor. 相似文献
10.
Yucai Zhu 《International journal of control》2013,86(18):1692-1702
Identification of single-input single-output Hammerstein models is studied in this work. The basic idea here is to extend the recently developed asymptotic method (ASYM) of linear model identification to include input non-linearity in the model set. First identification test design will be discussed. In parameter estimation, prediction error criterion is used in order to maintain consistence when the process is operating in closed-loop. A relaxation iteration scheme is proposed by making use of a model structure in which the error is bilinear in the parameters. The order of the linear part and nonlinear part are determined by looking at an output error related criterion which is control-relevant. The frequency domain upper error bound of the linear part will be derived and used for model validation. Simulation study will be used to illustrate the method and comparisons with other methods are also given. 相似文献
11.
对一类非线性离散时间系统提出了模糊辨识方法,此方法用与未知参数向量成线性关系的模糊逻辑系统作为辨识模型,并通过自适应学习律对此模糊逻辑系统中的未知参数进行自适应调节,文中证明了此方法可使辨识误差收敛到原点的一个邻域内。仿真结果验证了此方法的有效性。 相似文献
12.
针对线性和弱非线性振动系统进行了研究,提出采用非线性自回归时序(GNAR)模型进行系统频率辨识和判断系统性或非线性基本特征的方法。首先根据摄动法求解非线性微分方程的理论,论证GNAR模型与线性和弱非线性系统之间的本质联系,推导出GNAR模型系数与线性和非线性系统频率之间的解析关系,然后给出由GNAR模型系数和结构判断系统是否存在非线性,及辨识系统频率和非线性项基本特征的方法。最后,以单自由度线性振动系统和无阻尼Duffing振动系统为算例验证该辨识方法的有效性和准确性。实验结果表明,基于GNAR模型的振动系统基本特征辨识方法具有较好的识别精度,能用于估计系统的动力学特性。 相似文献
13.
Estimation of transfer functions of linear systems is one of the most common system identification problems. Several different design variables, chosen by the user for the identification procedure, affect the properties of the resulting estimate. In this paper it is investigated how the choices of prefilters, noise models, sampling interval, and prediction horizon (i.e., the use ofk -step ahead prediction methods) influence the estimate. An important aspect is thai the true system is not assumed to be exactly represented within the chosen model set. The estimate will thus be biased. It is shown how the distribution of bias in the frequency domain is governed by a weighting function, which emphasizes different frequency bands. The weighting function, in turn, is a result of the previously listed design variables. It is shown, e.g., thai the common least-squares method has a tendency to emphasize high frequencies, and that this can be counteracted by prefiltering. It is also shown that, asymptotically, it is only the prediction horizon itself, and not how it is split up into sampling interval times number of predicted sampling instants, that affects this weighting function. 相似文献
14.
On perceptual distortion minimization and nonlinear least-squares frequency estimation 总被引:1,自引:0,他引:1
Christensen M.G. Jensen S.H. 《IEEE transactions on audio, speech, and language processing》2006,14(1):99-109
In this paper, we present a framework for perceptual error minimization and sinusoidal frequency estimation based on a new perceptual distortion measure, and we state its optimal solution. Using this framework, we relate a number of well-known practical methods for perceptual sinusoidal parameter estimation such as the prefiltering method, the weighted matching pursuit, and the perceptual matching pursuit. In particular, we derive and compare the sinusoidal estimation criteria used in these methods. We show that for the sinusoidal estimation problem, the prefiltering method and the weighted matching pursuit are equivalent to the perceptual matching pursuit under certain conditions. 相似文献
15.
《Advances in Engineering Software (1978)》1988,10(4):195-201
This paper presents a computer-aided engineering approach for identification of linear models from a set of frequency response data. The approach is based on a new system identification technique. The primary intention of the developed system identification technique and the associated software is to identify linear models for nonlinear systems whose input/output behaviour is characterized by their corresponding sinusoidal-input describing function models. However, the technique may also be applied to identification of linear models from experimental frequency response data. At present, the identification approach and the associated software is limited to single-output, linear, deterministic, and time-invariant systems. A computer-aided engineering environment based on the developed system identification technique has also been developed. The software is developed on a Harris-800 super-minicomputer and a Tektronix 4115B high resolution, raster, and color graphics terminal. 相似文献
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17.
Auxiliary model-based least-squares identification methods for Hammerstein output-error systems 总被引:10,自引:0,他引:10
The difficulty in identification of a Hammerstein (a linear dynamical block following a memoryless nonlinear block) nonlinear output-error model is that the information vector in the identification model contains unknown variables—the noise-free (true) outputs of the system. In this paper, an auxiliary model-based least-squares identification algorithm is developed. The basic idea is to replace the unknown variables by the output of an auxiliary model. Convergence analysis of the algorithm indicates that the parameter estimation error consistently converges to zero under a generalized persistent excitation condition. The simulation results show the effectiveness of the proposed algorithms. 相似文献
18.
Daniel Cavalcanti Jeronymo Yuri Cássio Campbell Borges Leandro dos Santos Coelho 《Expert systems with applications》2011,38(11):13688-13693
Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi–Sugeno (TS) fuzzy model. TS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on TS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated TS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the TS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. 相似文献
19.
In reality, virtually every process is a nonlinear system. Nevertheless, linear controller design methods have proved to be adequate in many applications. In practice, the linear controller design is usually done disregarding a possible nonlinear plant/linear model mismatch. In this work we introduce a general framework for the development of linear controllers for nonlinear systems based on nonlinearity measures. Nonlinearity measures are tools to assess the extent of a system’s inherent nonlinearity instead of just recognizing a system as being linear or nonlinear. Recent work shows that nonlinearity measures characterize the magnitude of the modeling error when an optimal linear model is used for the nonlinear system. The best linear model can then be used to design a linear controller that robustly stabilizes the linear system in presence of the nonlinear modeling error. A crucial point is that both, the best linear model and the modeling error, are determined for a specified region of operation, thus significantly increasing the class of applicable nonlinear systems. Examples demonstrate the (necessity and) effectiveness of the proposed approach. 相似文献
20.
二次调节流量耦联系统为非线性系统, 在Volterra 级数描述该系统的基础上, 通过SISO多项式类非线性系统的GFRF 递推算式获得二次调节流量耦联系统的广义频率响应函数GFRF(generalized frequency response function). 基于系统的GFRF, 在频域内应用非线性控制理论为系统设计了镇定控制器和非线性H∞控制器, 不仅使系统稳定, 而且能达到无超调、无稳态误差. 此外, 在白噪声条件下证明该控制器比线性控制器抗干扰性强. 相似文献