Implementation and Evaluation of Online System Identification of Electromechanical Systems Using Adaptive Filters

• Published in: IEEE transactions on industry applications Vol. 52; no. 3; pp. 2306 - 2314
• Main Authors: Kshirsagar, Parag, Dong Jiang, Zhendong Zhang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Adaptive filters; Analyzers; Convergence; Dynamical systems; Dynamics; Electromechanical system; Electromechanical systems; Frequency response; Loads (forces); On-line systems; System identification; Transfer functions; electromechanical system; system identification; Adaptive filters
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2016.2515994

Online system identification method provides useful insight into the electromechanical plant behavior during commissioning as well as health monitoring. In addition to controller tuning, the methods can be applied for identifying mechanical modes or resonances, sensor vibrations, and unmodeled load dynamics. Online system identification using frequency response analysis is considered in this study. The focus of this paper will be on estimating the real-time frequency response of various systems using adaptive filters. For comparative evaluation, a commercial off-the-shelf spectrum analyzer is used. The essential aspects to be addressed for adaptive filter are: understanding the influence of convergence gain on accuracy of frequency response and selecting the frequency sweep rate. In this work, online system identification using frequency response is demonstrated on two setups: 1) magnetic levitation system and 2) permanent-magnet motor drive operating in sensorless mode. The experimental result validates that the method elaborated is simple, easy to implement, and accurate when compared with spectrum analyzer.