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Decomposition‐based over‐parameterization forgetting factor stochastic gradient algorithm for Hammerstein‐Wiener nonlinear systems with non‐uniform sampling

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0 Published in 2021 at "International Journal of Robust and Nonlinear Control"

DOI: 10.1002/rnc.5576

Abstract: This article investigates the parameter estimation problems of Hammerstein‐Wiener nonlinear systems with non‐uniform sampling. The over‐parameterization identification model for the Hammerstein‐Wiener nonlinear systems is established from the non‐uniformly sampled input‐output data. By applying the gradient… read more here.

Keywords: hammerstein wiener; nonlinear systems; forgetting factor; wiener nonlinear ... See more keywords

Hammerstein–Wiener modelling of a magneto-rheological dampers considering the magnetization dynamics

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0 Published in 2021 at "Control Engineering Practice"

DOI: 10.1016/j.conengprac.2021.104829

Abstract: Abstract Magneto-rheological dampers are an effective technology to control the damping coefficient of a semi-active suspension. Most of the contributions in literature propose damper models to be used in simulation, or as damping force virtual… read more here.

Keywords: control; rheological dampers; hammerstein wiener; magneto rheological ... See more keywords

Recursive parameter estimation for Hammerstein-Wiener systems using modified EKF algorithm.

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0 Published in 2017 at "ISA transactions"

DOI: 10.1016/j.isatra.2017.05.012

Abstract: This paper focuses on the recursive parameter estimation for the single input single output Hammerstein-Wiener system model, and the study is then extended to a rarely mentioned multiple input single output Hammerstein-Wiener system. Inspired by… read more here.

Keywords: parameter estimation; parameter; recursive parameter; hammerstein wiener ... See more keywords

A novel extreme learning Machine-based Hammerstein-Wiener model for complex nonlinear industrial processes

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0 Published in 2019 at "Neurocomputing"

DOI: 10.1016/j.neucom.2019.05.049

Abstract: Abstract In this paper, a novel extreme learning machine (ELM) based Hammerstein-Wiener model is developed for the approximation of complex nonlinear systems. The proposed model has two static ELM networks surround a dynamic linear part.… read more here.

Keywords: proposed model; wiener model; model; hammerstein wiener ... See more keywords

Multi-model predictive control of Hammerstein-Wiener systems based on balanced multi-model partition

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0 Published in 2019 at "Mathematical and Computer Modelling of Dynamical Systems"

DOI: 10.1080/13873954.2019.1624580

Abstract: ABSTRACT Model analysis of Hammerstein-Wiener systems has been made, and it is found that the included angle is applicable to such systems to measure the non-linearity. Then, a dichotomy gridding algorithm is proposed based on… read more here.

Keywords: multi model; control; model; partition ... See more keywords

Structured Hammerstein-Wiener Model Learning for Model Predictive Control

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0 Published in 2021 at "IEEE Control Systems Letters"

DOI: 10.1109/lcsys.2021.3077201

Abstract: This letter aims to improve the reliability of optimal control using models constructed by machine learning methods. Optimal control problems based on such models are generally non-convex and difficult to solve online. In this letter,… read more here.

Keywords: wiener model; control; structured hammerstein; optimal control ... See more keywords

Disturbance-Encoding-Based Neural Hammerstein–Wiener Model for Industrial Process Predictive Control

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1 Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"

DOI: 10.1109/tsmc.2020.3004382

Abstract: The control reliability of model predictive control is largely determined by the accuracy of the process model. The Hammerstein–Wiener (HW) model is an important nonlinear process modeling technique that has obtained great success in some… read more here.

Keywords: disturbance; model; predictive control; hammerstein wiener ... See more keywords

Hammerstein–Wiener Multimodel Approach for Fast and Efficient Muscle Force Estimation from EMG Signals

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2 Published in 2022 at "Biosensors"

DOI: 10.3390/bios12020117

Abstract: This paper develops a novel approach to characterise muscle force from electromyography (EMG) signals, which are the electric activities generated by muscles. Based on the nonlinear Hammerstein–Wiener model, the first part of this study outlines… read more here.

Keywords: emg signals; muscle force; force; approach ... See more keywords

Identification of Nonlinear Systems Using the Hammerstein-Wiener Model with Improved Orthogonal Functions

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0 Published in 2023 at "Elektronika ir Elektrotechnika"

DOI: 10.5755/j02.eie.33838

Abstract: Hammerstein-Wiener systems present a structure consisting of three serial cascade blocks. Two are static nonlinearities, which can be described with nonlinear functions. The third block represents a linear dynamic component placed between the first two… read more here.

Keywords: structure; orthogonal functions; improved orthogonal; wiener ... See more keywords