Fractional-order two-input two-output process identification based on Haar operational matrix

Abstract

The identification of multi-input-multi-output process is always challenging due to significant loop interactions. This article proposes an identification technique for two-input-two-output processes with fractional order models via Haar wavelet feature. The presented technique can estimate independent four fractional single-pole time delay models without additional steps to decouple processes during identification. The method uses a well-known relay feedback test to produce the input-output data for measurements. Then, the Haar wavelet operational matrix based algebraic approach is utilised to identify the unknown process models with reduced complexity. Numerical analysis on various examples show the efficacy even in presence of noise and without additional filter or preprocessing of measured signals. The comparative study proves advantages of the presented approach.

Keywords:

• TITO process
• fractional-order models
• identification
• Haar wavelet
• operational matrix

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Kajal Kothari

Kajal Kothari received the PhD degree in Electrical and Electronics Engineering from the University of the South Pacific, Fiji, and M.Tech. degree in Communication Systems from the Sardar Vallabhbhai National Institute of Technology, India. She is currently working with the School of Engineering and Physics, The University of the South Pacific, Fiji. Her research interests include image processing, system modeling and identification, and fractional systems and control.

Utkal Mehta

Utkal Mehta (SM’15) received the Ph.D. degree from IIT Guwahati, India, in the area of system identification and process control. He is now working in electrical and electronics engineering from The University of the South Pacific, Fiji as an Associate Professor. His current research interests include process identification, applied fractional calculus for modeling, fractional-order filter design on reconfigurable devices like FPAA and various robotics applications for medical and industrial automation.