Title :
Induction Machine Neural Estimator using Embedded System
Author :
Mouzinho, L.F. ; FonsecaNeto, J.V. ; Luciano, B.A. ; Freire, R.C.S. ; Catunda, Sebastian Y.
Author_Institution :
Dept. of Electron. & Electr. Eng., Maranhaos Fed. Center of Technologic Educ.
Abstract :
Indirect measurement architecture for speed estimation has been presented in this paper. This system is based on neural estimator implemented on programmable system on-chip (PSoC), using C++ language, which executes speed estimator algorithm, considering a 1.0 s time interval for neural estimator. The results from experiments and simulations indubitably proved the proposed estimator good performance. This efficiency was verified by analysis, considering the following focus: estimator precision when its compared to conventional speed measurements (tachometer). Speed measurements values from the PSoC and tachometer have shown a smaller than 2% discrepancy
Keywords :
C++ language; asynchronous machines; computerised instrumentation; embedded systems; neural nets; system-on-chip; tachometers; velocity measurement; C++ language; PSoC; embedded system; estimator precision; induction machine; neural estimator; programmable system on-chip; speed estimation; speed measurements; tachometer; Artificial neural networks; Embedded system; Induction machines; Neural networks; Observers; Signal processing algorithms; Software measurement; State estimation; Velocity measurement; Voltage; PSoC; embedded system; estimation; indirect measurement; neural networks; programmable architecture; speed Induction Machine; system real time;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2005. IMTC 2005. Proceedings of the IEEE
Conference_Location :
Ottawa, Ont.
Print_ISBN :
0-7803-8879-8
DOI :
10.1109/IMTC.2005.1604356
