ADALINE approach for induction motor mechanical parameters identification

نویسندگان

  • Hamid Sediki
  • Ali Bechouche
  • Djaffar Ould Abdeslam
  • Salah Haddad
چکیده

Two new methods to identify the mechanical parameters in induction motor based field oriented drives are presented in this paper. The identified parameters are: the moment of inertia and the viscous damping coefficient. The proposed methods are based on the adaptive linear neuron (ADALINE) networks. The two parameters are derived and optimised during the online training process. During the identification phase, the motor torque is controlled by the well-known field oriented control strategy. This torque is subjected to variations in order to obtain mechanical speed transients. The two proposed methods are simple to implement compared to the previous techniques. They require only the stator current and mechanical speed measurements. Finally, the effectiveness of the two methods and the accuracy of the derived parameters are proven experimentally by two direct starting tests. The originality of this work is the building of a model representation that it is suitable for implementation with ADALINE networks. This leads to a simple implementation and ease of mechanical parameters identification.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter valu...

متن کامل

Experimental Identification of the Mechanical Parameters of an Induction Motor Drive

In order to obtain fast dynamic response performance of an induction motor drive, the identification of mechanical parameters such as the drive inertia and the coefficients of friction, with a good accuracy, is highly desirable. They are essential for the design of the high-performance induction motor drive speed, as well as position controllers and speed observers, since a drive response is in...

متن کامل

Speed Observer Design for Linear Induction Motor Drives

In this paper, a neural network model reference adaptive system speed observer is designed, which can be used in speed control of linear induction motors (LIMs). Dynamical equations of LIM have been considered accurate. In other words, the end effect and the electrical losses of the motor have been included in the motor equivalent circuit. Then equations of the reference model and adaptive mode...

متن کامل

DSP Based Induction Motor Torque and Parameter Identification

Abstruct A practical induction motor torque and parameter measurement scheme is proposed without using any mechanical sensors. The torque and parameter calciulation is performed by a digital signal processor (DSP) based on measured motor terminal waveforms. Since the motor parameters are required for torque calculation, a novel scheme is developed for parameter identification. The motor paramet...

متن کامل

Computer Aided Design for Single-Phase Induction Motors Based on a New Gemoetrical Approach

Design of electrical motors normally involves two main stages: i) Preparation of the main dimensions and parameters. ii) Prediction of the performance. At the first stage the main dimensions of the motor, core stack Lfe and stator outer diameter Do, must be chosen. A set of performance conditions such as breakdown torque, desired output and other important parameters must satisfy the internatio...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Mathematics and Computers in Simulation

دوره 90  شماره 

صفحات  -

تاریخ انتشار 2013