Journal ArticleDOI
An iterative method for the identification of nonlinear systems using a Hammerstein model
Kumpati S. Narendra,P. Gallman +1 more
Reads0
Chats0
TLDR
In this article, an iterative method is proposed for the identification of nonlinear systems from samples of inputs and outputs in the presence of noise, which consists of a no-memory gain (of an assumed polynomial form) followed by a linear discrete system.Abstract:
An iterative method is proposed for the identification of nonlinear systems from samples of inputs and outputs in the presence of noise. The model used for the identification consists of a no-memory gain (of an assumed polynomial form) followed by a linear discrete system. The parameters of the pulse transfer function of the linear system and the coefficients of the polynomial non-linearity are alternately adjusted to minimize a mean square error criterion. Digital computer simulations are included to demonstrate the feasibility of the technique.read more
Citations
More filters
Journal ArticleDOI
Identification of continuous-time Hammerstein systems by simultaneous perturbation stochastic approximation
TL;DR: The main advantage of the SPSA-based method is that it can be applied to identification of Hammerstein systems with less restrictive assumptions, and is useful to obtain accurate models, even for high-dimensional parameter identification.
Journal ArticleDOI
A novel optimization algorithm for MIMO Hammerstein model identification under heavy-tailed noise.
TL;DR: This paper proposes a general identification method to solve the system identification of multi-input multi-output Hammerstein processes under the typical heavy-tailed noise based on a Gaussian-Mixture Distribution intelligent optimization algorithm (GMDA).
Journal ArticleDOI
On the Identification of Wiener Systems Having Saturation-like Functions with Positive Slopes
TL;DR: It is shown here that by a simple data reordering and by a following data partition the problem of identification of a nonlinear Wiener system could be reduced to a linear parametric estimation problem.
Proceedings ArticleDOI
On the identification of nonlinear maps in a general interconnected system
TL;DR: In this paper, the problem of identifying static nonlinear maps in a general, structured interconnected system is addressed by selecting the non-linear maps so as to maximize the "smoothness" or "staticness" of these maps.
Journal ArticleDOI
Suboptimal nonlinear predictive control based on multivariable neural Hammerstein models
TL;DR: A computationally efficient nonlinear Model Predictive Control (MPC) algorithm in which the neural Hammerstein model is used, which gives control performance similar to that obtained in nonlinear MPC, which hinges on non-convex optimization.
References
More filters
Journal ArticleDOI
A technique for the identification of linear systems
Kenneth Steiglitz,L. McBride +1 more
TL;DR: In this paper, an iterative technique is proposed to identify a linear system from samples of its input and output in the presence of noise by minimizing the mean-square error between system and model outputs.
Journal ArticleDOI
On the Identification Problem
TL;DR: In this paper, the identification of zero-memory multipoles and two-poles of class n_1 was studied, where the test signals are sine waves of different amplitudes and frequencies, and the measured quanity is the describing function of the device.