Title :
Integral Backstepping Control for a PMSM Drive Using Adaptive RNN Uncertainty Observer
Author :
Lin, Chih-Hong ; Lin, Ming-Kuan ; Wu, Ren-Cheng
Author_Institution :
Dept. of Electr. Eng., Nat. United Univ., Miaoli, Taiwan
Abstract :
Due to uncertainties exist in the applications of the permanent magnet synchronous motor (PMSM) servo drive which seriously influence the control performance. The integral back stepping controller and adaptive recurrent neural network uncertainty observer (RNNUO) is proposed to control the rotor of the PMSM to track periodic references in this paper. Firstly, the field-oriented mechanism is applied to formulate the dynamic equation of the PMSM servo drive. To further increase the robustness of the PMSM drive, an adaptive RNN uncertainty observer is proposed to estimate the required lumped uncertainty. Finally, the effectiveness of the proposed control scheme is verified by experimental results.
Keywords :
machine vector control; neurocontrollers; observers; permanent magnet motors; recurrent neural nets; robust control; synchronous motor drives; uncertain systems; PMSM drive robustness; PMSM rotor control; PMSM servo drive; RNNUO; adaptive RNN uncertainty observer; adaptive recurrent neural network uncertainty observer; dynamic equation; field-oriented mechanism; integral backstepping control; lumped uncertainty estimation; periodic reference tracking; permanent magnet synchronous motor; Adaptive systems; Backstepping; Control systems; Observers; Recurrent neural networks; Rotors; Uncertainty; integral backstepping control; permanent magnet synchronous motor; recurrent neural network;
Conference_Titel :
Computer, Consumer and Control (IS3C), 2012 International Symposium on
Conference_Location :
Taichung
Print_ISBN :
978-1-4673-0767-3
DOI :
10.1109/IS3C.2012.200
