Complete Identification of a Dynamic Fractional Order System Under Non-ideal Conditions Using Fractional Differintegral Definitions

TL;DR

This paper presents a novel method for accurately identifying fractional-order dynamical systems under realistic, noisy conditions using fractional calculus, enhancing control system modeling.

Contribution

It introduces a simple, effective parameter estimation scheme based on fractional calculus that works reliably with corrupted data, addressing real-world challenges.

Findings

High accuracy in parameter estimation despite data errors

Effective handling of non-ideal, real-life conditions

Applicable to a wide range of fractional-order systems

Abstract

This contribution deals with identification of fractional-order dynamical systems. System identification, which refers to estimation of process parameters, is a necessity in control theory. Real processes are usually of fractional order as opposed to the ideal integral order models. A simple and elegant scheme of estimating the parameters for such a fractional order process is proposed. This method employs fractional calculus theory to find equations relating the parameters that are to be estimated, and then estimates the process parameters after solving the simultaneous equations. The data used for the calculations are intentionally corrupted to simulate real-life conditions. Results show that the proposed scheme offers a very high degree of accuracy even for erroneous data.