Artificial Neural Network Control of Permanent Magnet Synchronous Motor
نویسنده
چکیده
This paper presents a neural network controller for permanent magnet synchronous motor (PMSM). The neural controller is used for torque ripple minimization of this type of motors. Two methods of neural controller design are used. The first method is based on two loop controllers (current controller and speed controller). The second method is based on estimation of torque constant and stator resistance in PMSM. The q-axis inductance is modeled off-line according to q-axis stator current. The neural weights are initially chosen small randomly and a model reference control algorithm adjusts those weights to give the optimal values. The neural network parameter estimator has been applied to flux linkage torque ripple minimization of the PMSM. Simulation results using the two methods are compared together. Moreover, the suggested algorithms when compared with other controllers show great success in torque ripples
منابع مشابه
Performance Improvement of Direct Torque Controlled Interior Permanent Magnet Synchronous Motor Drives Using Artificial Intelligence
The main theme of this paper is to present novel controller, which is a genetic based fuzzy Logic controller, for interior permanent magnet synchronous motor drives with direct torque control. A radial basis function network has been used for online tuning of the genetic based fuzzy logic controller. Initially different operating conditions are obtained based on motor dynamics incorporating...
متن کاملNovel Unified Control Method of Induction and Permanent Magnet Synchronous Motors
Many control schemes have been proposed for induction motor and permanent magnet synchronous motor control, which are almost highly complex and non-linear. Also, a simple and efficient method for unified control of the electric moto are rarely investigated. In this paper, a novel control method based on rotor flux orientation is proposed. The novelties of proposed method are elimination of q-ax...
متن کاملAdaptive Position Control of Permanent Magnet Synchronous Motor Drives using Neural Networks
A method is presented for position control of a permanent magnet synchronous motor (PMSM). First a linear descretized state-space model of a PMSM with unknown parameters is identified; the identified model is then controlled using state feedback with integrator techniques. The simulation results of a typical motor are obtained and the influence of pole placement, noise and load variations is st...
متن کاملA Discrete-time Vs Controller Based on Rbf Neural Networks for Pmsm Drives
A method merging the features of variable structure control and neural network design is presented for speed control of a permanent magnet synchronous motor. The proposed control approach is based on a discrete-time variable structure control and a robust digital differentiator for speed estimation. Radial basis function neural networks are used to learn about uncertainties affecting the system...
متن کاملThe Implementation of Permanent Magnet Synchronous Motor Speed Tracking Based on Onlineartificial Neural Network
This paper deals with the performance analysis of the field oriented control for a permanent magnet synchronous drive system with an artificial neural network proportional-integral-derivative for speed control in closed loop operation. Space vector pulse width modulation is used to generate the required stator voltage. The space vector pulse width modulation has the character of wide linear ran...
متن کاملPosition Control Improvement of Permanent Magnet Motor Using Model Predictive Control
Fast and accurate transient response is the main requirement in electric machine position control. Conventional cascade control structure has sluggish response due to the limitation of inner control loop bandwidth. In this paper, in order to decrease the Permanent Magnet Synchronous Motor (PMSM) transient response time it can be used reference model using feed-forward signals. In this structure...
متن کامل