ELM-based sensorless speed control of permanent magnet synchronous machine. (1st January 2013)

• Record Type: Journal Article
• Authors: Kumar, Vikas; Gaur, Prerna; Mittal, A.P.; Singh, Bhim
• Is Part Of: International journal of vehicle autonomous systems. Volume 11:Number 2/3(2013)
• Page Start: 190
• Page End: 204
• Publication Date: 2013-01-01
• Subjects: artificial neural network -- ELM -- extreme learning machine -- PMSM -- Permanent magnet synchronous machine -- BP -- back propagation -- sensorless control; Autonomous vehicles -- Periodicals; Motor vehicles -- Technological innovations -- Periodicals; Motor vehicles -- Electronic equipment -- Periodicals; Robots -- Control systems -- Periodicals; Intelligent transportation systems -- Periodicals; 629.20285
• Languages: English
• ISSNs: 1471-0226

Abstract

This paper deals with Extreme Learning Machine (ELM) based sensorless speed estimation and speed control of Permanent Magnet Synchronous Machines (PMSMs). ELM, first proposed by G.B. Huang as a new class of learning algorithm for Single-Hidden Layer Feedforward Neural Networks (SLFNs), is extremely fast and accurate, and has better generalisation performance than the traditional gradient-based training methods. To implement Field-Oriented Control (FOC) in PMSMs, the stator magnetic field is always kept 90 degrees ahead of the rotor. This requires rotor position information all the time. This information is accurately obtained with an ELM-based observer without the position sensor for PMSMs, and hence, the cost of the system is reduced, while the problems associated with the sensors are minimised.