Authors:
L. Niewiara
1
;
T. Tarczewski
1
and
L. M. Grzesiak
2
Affiliations:
1
Nicolaus Copernicus University, Poland
;
2
Warsaw University of Technology, Poland
Keyword(s):
Artificial Neural Network, Adaptive State Feedback Controller, Permanent Magnet Synchronous Motor, Torque Ripple.
Related
Ontology
Subjects/Areas/Topics:
Engineering Applications
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Neural Networks Based Control Systems
;
Optimization Algorithms
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
This paper deals with the problem of torque ripple minimization of permanent magnet synchronous motor. The novelty of the presented approach lays in precisely maintain the level of the voltage source inverter DC voltage demanded for proper operation of the motor. An additional voltage matching circuit with state feedback controller is introduced in order to control of the inverter DC voltage. In the proposed solution model of a plant (i.e. permanent magnet synchronous motor fed by voltage source inverter with additional voltage matching circuit) is non-linear and non-stationary. An adaptive state feedback controller is developed by using an artificial neural network, which approximates non-linear control gain surfaces. A simple adaptation algorithm based on 2 low-order low-pass filters is used. Simulation results illustrate the proposed approach in comparison to typical drive with voltage source inverter and stationary state feedback controller.