Abstract

The Nonlinear Frequency Response (NFR) method is a useful Process Systems Engineering tool for developing experimental techniques and periodic processes that exploit the system nonlinearity. The basic and most time-consuming step of the NFR method is the derivation of frequency response functions (FRFs). The computer-aided Nonlinear Frequency Response (cNFR) method, presented in this work, uses a software application for automatic derivation of the FRFs, thus making the NFR analysis much simpler, even for systems with complex dynamics. The cNFR application uses an Excel user-friendly interface for defining the model equations and variables, and MATLAB code which performs analytical derivations. As a result, the cNFR application generates MATLAB files containing the derived FRFs in a symbolic and algebraic vector form. In this paper, the software is explained in detail and illustrated through: (1) analysis of periodic operation of an isothermal continuous stirred-tank reactor with a simple reaction mechanism, and (2) experimental identification of electrochemical oxygen reduction reaction.

Highlights

  • Knowledge about process dynamics is crucial in chemical engineering, as well as in other engineering fields

  • Problem Formulation cNFRFormulation application will be illustrated in the case of electrochemical oxygen reduction

  • The computer-aided Nonlinear Frequency Response (cNFR) application will be illustrated in the case of electrochemical oxygen reduction

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Summary

Introduction

Knowledge about process dynamics is crucial in chemical engineering, as well as in other engineering fields. One of the useful tools for investigating process dynamics is frequency response (FR) [1,2,3,4,5,6,7]. FR is a response of the investigated system to sinusoidal input modulation and it enables defining a convenient model form in the frequency domain, usually called frequency transfer function or frequency response function [8]. The great majority of real systems are nonlinear, so nonlinear tools are necessary for their analysis. One such tool is the nonlinear frequency response method, which is used in this paper

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