نتایج جستجو برای: nonlinear system identification

تعداد نتایج: 2664976  

2013
XIANFANG WANG YUANYUAN ZHANG

This paper proposed a method to identify nonlinear systems via the fuzzy weighted least squares support machine (FW-LSSVM). At first, we describe the proposed modeling approach in detail and suggest a fast learning scheme for its training. Because the training sample data of independent variable and dependent variable has a certain error, and we obtain the sample which has a certain fuzziness f...

2008
JOSÉ DE JESÚS FERREYRA RAMÍREZ CARLOS AVILÉS-CRUZ IVAN VAZQUEZ-ALVAREZ

A new on-line clustering fuzzy neural network is proposed. In the algorithm, structure and parameter learning are updated at the same time. There is not difference between structure learning and parameter learning. It generates groups with a given radius. The center is updated in order to get that the center is near to the incoming data in each iteration, in this way, It does not need to genera...

2004
Amir Atiya Alexander Parlos

The so-called spatiotemporal neural network is considered. This is a neural network where the conventional weight multiplication operation is replaced by a linear filtering operation [l]. A training algorithm is derived for such networks. The problem of nonlinear system identification is considered as an application for spatiotemporal networks. Nonlinear system identification is one of the chal...

2016
Shazia Javed Noor Atinah Ahmad

In this paper, an efficient Kernel based algorithm is developed with application in nonlinear system identification. Kernel adaptive filters are famous for their universal approximation property with Gaussian kernel, and online learning capabilities. The proposed adaptive step-size KLMS (ASS-KLMS) algorithm can exhibit universal approximation capability, irrespective of the choice of reproducin...

2012
Ieroham S. Baruch Sergio M. Hernandez Jacob Moreno-Cruz Elena Gortcheva

A new Modular Recurrent Trainable Neural Network (MRTNN) has been used for system identification of two-mass-resort-damper nonlinear oscillatory plant. The first MRTNN module identified the exponential part of the unknown plant and the second one the oscillatory part of the plant. The plant has been controlled by a direct adaptive neural control system with integral term. The RTNN controller us...

2008
Fabien Lauer Gérard Bloch

Hybrid system identification aims at both estimating the discrete state or mode for each data point, and the submodel governing the dynamics of the continuous state for each mode. The paper proposes a new method based on kernel regression and Support Vector Machines (SVM) to tackle this problem. The resulting algorithm is able to compute both the discrete state and the submodels in a single ste...

Journal: :EURASIP J. Adv. Sig. Proc. 2009
Jarlath Ifiok Umoh Tokunbo Ogunfunmi

The primary difficulty in the identification of Hammerstein nonlinear systems (a static memoryless nonlinear system in series with a dynamic linear system) is that the output of the nonlinear system (input to the linear system) is unknown. By employing the theory of affine projection, we propose a gradient-based adaptive Hammerstein algorithm with variable step-size which estimates the Hammerst...

2007
Jozef Vörös

The class of nonlinear dynamic systems which can be represented by the block-oriented models, ie, by interconnection of linear dynamic and nonlinear static subsystems, has been studied by many authors. In the simplest case the models consist of a combination of two blocks giving the so-called Hammerstein (nonlinear-linear) and Wiener (linear-nonlinear) models and there are many methods for nonl...

Abdelaziz Aouiche Farid Bouttout Kheireddine Chafaa

The problem of disturbance rejection in the control of nonlinear systems with additive disturbance generated by some unforced nonlinear systems, was formulated and solved by {itshape Mukhopadhyay} and {itshape Narendra}, they applied the idea of increasing the order of the system, using neural networks the model of multilayer perceptron on several systems of varying complexity, so the objective...

2006
Ulrich Nehmzow Otar Akanyeti Roberto Iglesias Theocharis Kyriacou Stephen A. Billings

In mobile robotics, it is common to find different control programs designed to achieve a particular robot task. It is often necessary to compare the performance of such controllers. So far this is usually done qualitatively, because of a lack of quantitative behaviour analysis methods. In this paper we present a novel approach to compare robot control codes quantitatively, based on system iden...

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