Showing posts with label Control Theory. Show all posts
Showing posts with label Control Theory. Show all posts

Tuesday, February 7, 2017

SPEED AND TORQUE CONTROL OF AN INDUCTION MOTOR WITH ANN BASED DTC

Author :  Fatih Korkmaz
  

Volume, Issue, Month, Year :
 Vol.7, No.1, January 2017

ABSTRACT

 Due to advantages such as fast dynamic response, simple and robust control structure, direct torque control (DTC) is commonly used method in high performance control method for induction motors. Despite mentioned advantages, there are some chronically disadvantages with this method like high torque and current ripples, variable switching behaviour and control problems at low speed rates. On the other hand, artificial neural network (ANN) based control algorithms are getting increasingly popular in recent years due to their positive contribution to the system performance. The purpose of this paper is investigating of the effects of ANN integrated DTC method on induction motor performance by numerical simulations. For this purpose, two different ANN models have been designed, trained and implemented for the same DTC model. The first ANN model was designed to select optimum inverter and the second model was designed to use in the determination of the flux vector position. Matlab/Simulink model of the proposed ANN based DTC method was created in order to compare with the conventional DTC and the proposed DTC methods. The simulation studies proved that the induction motor torque ripples have been reduced remarkably with the proposed method and this approach can be a good alternative to the conventional DTC method for induction motor control.


CALIBRATION OF INERTIAL SENSOR BY USING PARTICLE SWARM OPTIMIZATION AND HUMAN OPINION DYNAMICS ALGORITHM

Author :  Vikas Kumar Sinha , Avinash Kumar Maurya
  

Volume, Issue, Month, Year :
 Vol 7, No 1, January, 2017

ABSTRACT

An Inertial Navigation System (INS) can easily track position, velocity and orientation of any moving vehicle. Generally, deterministic errors are present in an uncalibrated Inertial Measurement Unit (IMU) which leads to the requirement of an accurate estimation of navigation solution. These inertial sensors, thus, needs to be calibrated to reduce the error inherent in these systems. By mathematical model of IMU including both accelerometer and gyroscope is utilized for the purpose of error calibration. Particle Swarm Optimization (PSO) and Human Opinion Dynamics (HOD) Optimization based calibration techniques have used to obtain error parameters such as bias, scale factor and misalignment errors.