Artificial neural network based controller for line starting performance synchronous motor of a conveyor system using field oriented self-controlled
This paper presents the design process of a synchronous motor of conveyor system using field oriented control of line starting [1]. The preliminary design is d-q model armature rotor line start synchronous motor with field oriented control for decreasing a starting current and torque. The design all...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2016
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/73091/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991108535&doi=10.1109%2fICSIMA.2015.7559013&partnerID=40&md5=b018886ee17b45276e713fd292c9eb30 |
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| Summary: | This paper presents the design process of a synchronous motor of conveyor system using field oriented control of line starting [1]. The preliminary design is d-q model armature rotor line start synchronous motor with field oriented control for decreasing a starting current and torque. The design allows the motor to operate at both starting and synchronous speed. The basic equations for park-clark transformation of the rotor-stator for proposed field oriented self-controlled to synchronous motor are presented [2]. The starting performance of synchronous motor, for example in conveyor application, requires rapid dynamics and precise regulation; hence the need of direct control is becoming an urgent demand. This type of control provides an independent field oriented self-controlled of torque and current, which is similar to a separately excited synchronous motor and offers a number of attractive features. Synchronous motor has a high starting torque while separately synchronous motor can operate above the base low speed in the line starting current [3]. This paper designs study and highlights the effectiveness of the proposed field oriented control methods for a line starting performance of synchronous motor model parameter, using artificial neural network methods both simulation and manufacturers measured experimental data. A steady state and transient analysis of the synchronous motor is performed below and above base line starting current. |
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