Bezsenzorski pogon za vuču s estimatorima u kliznom režimu i MRASCC-u koristeći izravno upravljanje momentom

In the paper two types of speed, torque and flux estimators are described. The Sliding Mode Observer (SMO) and the Model Reference Adaptive System (MRAS) type estimators are applied in the sensorless Direct Torque Control with Space Vector Modulation algorithm (DTC-SVM) of Induction Motor (IM) drive. Dynamical performance of the drive and the estimator properties in field weakening and low speed regions for traction drive system are presented.U članku su opisana dva tipa estimatora brzine, momenta i toka – observer u kliznom režimu (SMO) i adaptivni sustav reference modela (MRAS). Oba tipa estimatora su primijenjena u bezsenzorskom izravnom upravljanju momentom s modulacijom prostornih vektora (DTC-SVM) na pogonu s asinkronim motorom (IM). Prikazane su dinamičke karakteristike pogona i estimatora u režimima slabog polja i male brzine za slijedni sustav

Fault tolerant direct torque control of induction motor with adaptive neuro-fuzzy controller

In the paper the possibility of adaptive neuro-fuzzy controller application in the Direct Torque Controlled (DTC-SVM) induction motor drive system was presented. Simulation results of the vector controlled induction motor drive system during the speed sensor faults were illustrated. System was checked during the control topology changes. Control structure was tested and checked during different drive operations. Simulation results were obtained using Sim Power System

Induction motor rotor faults detection based on neural networks in direct field oriented control structure

In the paper the influence of broken rotor bars to the properties of vector controlled induction motor drive system was checked. Characteristic frequency was shown. The rotor fault detector based on the neural network was described and tested in simulation. Proposed algorithm was applied in the Direct Field Oriented Control Structure of Induction Motor. Control structure was tested and checked during different drive operation. Simulation results were performed in Matlab Simulink software

Sensorless direct torque control of induction motor with adaptive neuro-fuzzy compensator

The possibility of application the adaptive neuro-fuzzy controller in the structure of Direct Torque Control as a so-called neuro-fuzzy speed compensator are presented in the paper. In the paper the simulation and experimental results of the vector controlled induction motor drive system under different conditions are presented. The simulation tests carried out in Matlab/Sim Power System software, DS1103 card is applied in the experimental tests

Experimental tests of the MRASCC estimator with neural speed adaptation mechanism

In this paper MRASCC (Model Reference Adaptive System) model applied for estimation of rotor flux and angular speed of induction machine is presented. The main part of analysed system consist of current model and rotor circuit simulator. Adaptation of speed value is realised based on obtained signals using ADALINE (Adaptive Linear Neuron). In article mathematical description and experimental verification of theoretical considerations is presented. Estimator is tested in field oriented control structure. Moreover, researches of analysed model, in case of inaccurate information about electrical and mechanical parameters of the drive, are presented

Analyzis of hybrid electrical vehicle with induction motor

This paper presents an possibility of Direct Torque Control of Induction Motor Drive application in a Hybrid Electrical Vehicle. Control structure with and without external speed control loop was tested and checked during different drive operation. Simulation results were performed in Sim Power System software

Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator

This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct rotor-field oriented control (DRFOC) of the induction motor (IM) drive structure. Connective weights of the controller are trained on-line according to the error between the actual speed of the drive and the reference model output signal. The rotor flux and speed of the vector controlled induction motor are estimated using the model reference adaptive system (MRAS) – type estimator. Presented simulation results are verified by experimental tests performed on the laboratory-rig with DSP controller

An influence of the chosen sensors faults to the performance of induction motor drive system working in vector control method

W artykule przedstawiono analizę układu napędowego z silnikiem indukcyjnym pracującym w strukturze sterowania polowo zorientowanego DFOC podczas uszkodzeń wybranych czujników pomiarowych. Zwrócono szczególną uwagę na wpływ uszkodzeń na przebiegi wybranych zmiennych stanu napędu indukcyjnego oraz na możliwość ich wykorzystania do diagnostyki napędu elektrycznego. Badania symulacyjne wykonano w środowisku Matlab/SimPowerSystem. Zaproponowane rozwiązanie może być z powodzeniem wykorzystane w systemach o zwiększonym stopniu bezpieczeństwa.In the paper the influence of the chosen sensors faults (rotor speed and stator current sensors) to the properties of induction motor drive system working in the Direct Field Oriented Control structure (DFOC) were tested. Study results of simulations carried out in Matlab/SimPowerSystem software in various states of motor drive are presented. Study results contains an analysis of the state variables such as: mechanical and estimated speed, electromagnetic torque, stator's phase currents and rotor flux. Additionally the usage of these signals to develop faults detection algorithms were tested

Fault tolerant drive system with adaptive neuro–fuzzy compensator

W artykule przedstawiono możliwości wykorzystania adaptacyjnego regulatora neuronowo rozmytego (ANFC – Adaptive Neuro-Fuzzy Controller) pracującego w charakterze kompensatora, w układzie bezpośredniego sterowania momentem elektromagnetycznym (DTC-SVM – Direct Torque Control)) silnika indukcyjnego o zwiększonym stopniu bezpieczeństwa. Wykonano badania ilustrujące wpływ połączenia układu adaptacyjnego z klasycznym regulatorem liniowym typu PI w torze regulacji prędkości kątowej na jakość pracy napędu podczas zmiany topologii sterowania, wywołanej uszkodzeniem czujnika prędkości kątowej. Badania wykonano w środowisku Sim Power System.In the paper the fault tolerant drive system with adaptive neuro – fuzzy compensator (ANFC) is presented. The Direct Torque Control algorithm was applied and tested during the faulted conditions. Simulation results of the vector controlled induction motor drive with PI controller and ANFC during the topology changing is presented. To the flux and rotor speed reconstruction MRAS type estimator is used. Simulation results are performed in Sim Power System

Influence of IGBT transistor fault in frequency inverter to the performance of the induction motor drive

This paper presents a influence of IGBT transistor fault to the performance direct field oriented control DFOC and direct torque control DTC-SVM of induction motor drive. Study results of the open-switch fault that were presented, contains an analysis of the state variables such as: mechanical speed, electromagnetic torque, stator’s phase currents, rotor or stator flux