| Full text | |
| Author(s): |
dos Santos, Tiago Henrique
[1]
;
da Silva, Ivan Nunes
[2]
;
Goedtel, Alessandro
[3]
;
Castoldi, Marcelo Favoretto
[3]
;
Angelico, Bruno Augusto
[4]
Total Authors: 5
|
| Affiliation: | [1] Fed Inst Parana, Dept Control & Ind Proc, Ave Civica, Assis Chateaubriand, PR - Brazil
[2] Univ Sao Paulo, Sao Carlos Sch Engn, Dept Elect Engn, Ave Trabalhador Sao Carlense 400, Sao Carlos, SP - Brazil
[3] Fed Technol Univ Parana, Dept Elect Engn, Ave Alberto Carazzai, Cornelio Procopio, PR - Brazil
[4] Univ Sao Paulo, Dept Telecomm & Control Engn, Escola Politecn, Ave Prof Luciano Gualberto, Travessa 3, BR-158 Sao Paulo, SP - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | SOFT COMPUTING; v. 25, n. 20, p. 12977-12988, OCT 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
The direct measurement of speed in induction motors is costly and requires maintenance. Thus, sensorless techniques for estimating or predicting the speed in three-phase induction motors represent a feasible and economical solution. This work considers a single time delay neural network as a speed estimator in two different strategies of stator field-oriented induction motor drive: direct current and torque control. Time delay neural network makes the estimated signal robust against noise, that is usually found in switched power systems, and against disturbances on the input signals, since the estimator is not dependent only on instantaneous values. The synchronous speed and the electromagnetic torque, which are usual quantities in field oriented drives, are the inputs of the proposed neural estimator. In order to have a robust estimator facing induction motor parameter variations, the procedure of training and validating the neural networks are conducted with three different induction motors, from simulations to the experimental tests. An embedded system is also presented, and the scheme is tested considering various speed and load torque levels with different control strategies. (AU) | |
| FAPESP's process: | 11/17610-0 - Monitoring and control of dynamic systems subject to faults |
| Grantee: | Roberto Kawakami Harrop Galvão |
| Support Opportunities: | Research Projects - Thematic Grants |