NEURAL STATE FILTERING FOR ADAPTIVE INDUCTION MOTOR SPEED ESTIMATION

✍ Scribed by R.M. BHARADWAJ; A.G. PARLOS

• Publisher: Elsevier Science
• Year: 2003
• Tongue: English
• Weight: 395 KB
• Volume: 17
• Category: Article
• ISSN: 0888-3270
• DOI: 10.1006/mssp.2002.1523

✦ Synopsis

Effective sensorless transient speed estimation of induction motors is desirable for both on-line condition monitoring and assessment, and for efficiency calculations. In this paper, a sensorless neural adaptive speed filter is developed for induction motors operating under normal conditions and running off the power supply mains. The filter performance is demonstrated by comparisons with speed sensor measurements and spectral speed estimates. In addition to nameplate information required for initial filter set-up, the proposed neural speed filter uses only measured motor terminal currents and voltages. Initial training of the speed filter is accomplished off-line, using rotor slot harmonic-based speed estimates. The developed speed filter is scalable and it has been used for speed estimation of induction motors with varying power ratings. Incremental tuning is used to further improve filter performance and reduce filter development time significantly.