학술논문

Relevance of accurate filter design in Hammerstein model identification algorithms of nonlinear systems
Document Type
Conference
Source
2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) Electrical, Computer and Energy Technologies (ICECET), 2021 International Conference on. :1-5 Dec, 2021
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Finite impulse response filters
Computational modeling
Low-pass filters
Prototypes
IIR filters
Reliability
Object recognition
nonlinear systems
Hammerstein model
pulse compression
noise reduction
Language
Abstract
The Hammerstein model proved to be very effective in the representation of nonlinear systems. The identification of its kernels is possible through a reliable and computationally light procedure which can be further improved through the use of low-pass filters: this latter technique has been proposed based on the use of FIR filters, which, in the application in object, need a number of coefficients in the order of one thousand. In the present paper we verify the possibility to implement lowpass filtering using IIR structures, which are characterized by a drastically lower number of parameters. In the paper we consider in particular lowpass filters derived from analogue prototypes of Butterworth and Chebyshev types, and we compare their results with those obtainable through the use of FIR filters. The results presented here, verified in an experimental situation, provide the designer of the processing system with useful tools for an optimization of the Hammerstein model identification system.