Adaptive neural network control of chaos in permanent magnet synchronous motor. Issue 3 (2nd July 2016)

• Record Type: Journal Article
• Authors: Aguilar-Mejía, Omar; Tapia-Olvera, Rubén; Valderrabano-González, Antonio; Rivas Cambero, Iván
• Is Part Of: Intelligent automation & soft computing. Volume 22:Issue 3(2016)
• Page Start: 499
• Page End: 507
• Publication Date: 2016-07-02
• Subjects: Permanent magnet synchronous machine -- chaos -- neural network -- spline function -- speed control; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 003.5
• DOI: 10.1080/10798587.2015.1103971
• Languages: English
• ISSNs: 1079-8587

Abstract

Abstract: Permanent magnet synchronous motors have been used as variable-speed drives, especially for speed control and position, but it exhibits chaotic performance under certain parameter's changes. This work presents the use of a B-Spline neural network scheme to stabilize chaos and to adjust the rotor speed of synchronous motors. The B-spline neural network is an efficient tool to implement the adaptive speed control, with the possibility of carrying out this task on-line, taking into account the systems non-linearities. One of the main tasks is the adjustment of the proportional-integral parameters for rotor speed controller. In this work, a neural network algorithm is used to solve this problem. A nonlinear observer is designed for estimation of the rotor speed and load torque. The results of numerical simulations demonstrate that the permanent magnet synchronous motors with the B-Spline control scheme has a good dynamic performance and steady state accuracy.