Nonlinear Model Of Induction Motor Research Articles

A Mathematical Model of a Three-Phase Induction Motor with a Phase Rotor

A mathematical model of an induction motor (IM) with a phase rotor is developed on the basis of the usual assumptions that does not use the supposition that there is an annular rotating field in its air gap and various transformations of coordinates. The model is valid for both transient and steady-state modes and with various ways of control by changing the parameters of the three-phase feeding voltage system of the IM stator coil. It is shown that the desired stationary operation mode that exists in the developed nonlinear IM model at a constant feeding voltage of the stator and load torque corresponds to the constant electromagnetic torque and spinning frequency of the rotor at sine-wave rotor and stator currents. A digital IM model is developed in the MATLAB system. An analytical solution is derived for the system of linear differential equations that describes the IM with a retarded rotor and allows evaluating the nonlinear digital model for correctness. Examples of applying the IM model in analyzing transient and steady-state operation modes of this motor are provided.

A fuzzy type-2 fault detection methodology to minimize false alarm rate in induction motor monitoring applications

Automatic routines for Fault Detection and Diagnosis (FDD) are very important in industrial monitoring systems. However, false alarms potentially occur. High false alarm rates may lead to outages and consequent losses in the production process. To address such problem, a new FDD strategy based on type-2 fuzzy systems is proposed herein to minimize the false alarm rate. By applying system identification techniques, parametric models are estimated in order to represent the operation of the system under several levels of fault severity. The test system is a detailed dynamic nonlinear model of induction motor drive. The faults considered were partial short-circuit in stator winding coils. A performance comparison was made by implementing the monitoring system with both a type-2 fuzzy system interval and a type-1 fuzzy system. The results obtained thereby showed the improved performance and robustness of type-2 fuzzy system-based monitoring system, which outdoes the performance obtained by a type-1 fuzzy system. Furthermore, the performance of the proposed type-2 fuzzy system-based monitoring system may be further improved by using a Genetic Algorithm for tuning the parameters of the fuzzy type-2 system.

Design and Implementation of a Feedback Linearization Controlled IM Drive via Simplified Neuro-Fuzzy Approach

ABSTRACTThis research paper introduces an outline of a simplified version of single-input neuro-fuzzy controller (NFC) method via a decoupling-controlled intuitive feedback linearization (FBL) approach of induction motor (IM) model. The proposed NFC with FBL extensively reduces the torque and speed ripple along with better performance enhancement. A simplified state-space feedback linearization technique-based nonlinear IM model is designed and simulated in the stationary reference frame. Again, the parameter and plant uncertainties in the feedback-linearized model of the IM are continuous phenomenon which led to the design of a robust, simplified NFC to overcome these issues in the real-time industrial application. The proposed reduced membership function (MF) based simplified NFC is the integration of fuzzy logic and neural network concept with single input as an error (speed and torque) unlike two inputs error and change in error of conventional NFC. This has the advantage of improving the computational efficiency due to its simple structure and robustness over conventional NFC. This makes the system easy and simple to implement in a realistic situation. The performance and effectiveness of the proposed method using FBL concept of IM drive is analyzed using MATLAB software in different modes of operation and is distinguished with the conventional PI-controller and conventional NFC to show its superiority. The proposed system with the different control strategies is also validated by extensive experimental results using DSP 2812.

Advanced Integrated Modeling and Analysis for Adjustable Speed Drives of Induction Motors Operating With Minimum Losses

The nonlinear induction motor model is appropriately integrated by incorporating the dynamics of the power electronic converter in a manner that permits the design of stable field-oriented control (FOC) operating with minimum losses. As already proven, the challenging issue of operating the induction machine with minimum copper losses requires a varying rotor flux opposed to the standard FOC technique, which keeps the rotor field magnitude constant and tracks the electric torque to the desired level. To this end, exploiting the Hamiltonian structure of the developed motor/converter model, an innovated nonlinear controller is proposed that guarantees the technical limits of the converter (linear modulation) and simultaneously operates under FOC at steady state to achieve accurate speed regulation with varying rotor flux according to the minimal losses requirements. Under these circumstances, the conventional FOC stability analysis does not hold anymore, and therefore for the first time, a new rigorous analysis is provided that proves stability and convergence to the desired equilibrium for the complete closed-loop motor converter system. Finally, the theoretical contribution is examined in comparison to the traditional FOC operation by simulations obtained for an industrial size induction motor, while it is further evaluated by real-time results of a motor with similar parameters.

Implementation of a new fuzzy vector control of induction motor

The aim of this paper is to present a new approach to control an induction motor using type-1 fuzzy logic. The induction motor has a nonlinear model, uncertain and strongly coupled. The vector control technique, which is based on the inverse model of the induction motors, solves the coupling problem. Unfortunately, in practice this is not checked because of model uncertainties. Indeed, the presence of the uncertainties led us to use human expertise such as the fuzzy logic techniques. In order to maintain the decoupling and to overcome the problem of the sensitivity to the parametric variations, the field-oriented control is replaced by a new block control. The simulation results show that the both control schemes provide in their basic configuration, comparable performances regarding the decoupling. However, the fuzzy vector control provides the insensitivity to the parametric variations compared to the classical one. The fuzzy vector control scheme is successfully implemented in real-time using a digital signal processor board dSPACE 1104. The efficiency of this technique is verified as well as experimentally at different dynamic operating conditions such as sudden loads change, parameter variations, speed changes, etc. The fuzzy vector control is found to be a best control for application in an induction motor.

High Performance Direct Torque and Flux Control of Induction Motor Drive Using Fuzzy Logic Based Speed Controller

In this research study, direct torque and flux control of induction motor drive (IMD) using fuzzy logic based speed controller (FLSC) is implemented to minimize the ripple contents of stator current, flux and torque and also improve the speed responses under transient and steady state operating conditions. It is quite difficult to optimize the high performance of an IMD using conventional PI- speed controller (PISC), because of the nonlinear model of induction motor drive. The conventional PI-controller requires accurate and continuous tuning of gain values. Therefore, the FLC technique is implemented to improve the system performance. The detailed simulation results are presented in forward and reversal motoring under 1200 rpm and 900 rpm with no-load, load, sudden change in speed and sudden zero speed operating conditions using MATLAB/Simulink software to support the feasibility of the control strategy. To validate the FLSC control approach, the system is also implemented on real-time system and adequate results are reported for its validation

Feedback control for the discrete non-linear model of induction motor drives

An investigation is made of the stability for the discrete control of drives using a frequency induction motor as an actuator. The approach proposed is based on the choice of a particular model of the discretized system which is non-linear in the state and linear in the control. Because the model parameters depend only on the value of the slip angular frequency, the stabilizing control law is obtained by considering the non-linear time-invariant system as a linear time-varying one. As a consequence, the feedback control is a linear function of the state variables with coefficients depending on the actual values of the time-varying system parameters. The difficulty for computing these coefficients in line is overcome by proposing a suitable choice of constant feedback coefficients, which, for the case of the induction motor, give very efficient and satisfactory results.