Design and Simulation of an Efficient Neural Network Based Speed Controller For Vector Controlled Induction Motor Drive

This project work start with the development of simulation model of rotor magnetic field oriented vector control system based on MATLAB software. This paper proposes the development of a Neural Network controller in place of PI controller commonly used in the vector control structure for efficient speed control and smaller settling time. After successful implementation of proposed Neural Network controller, the results obtained, which shows the superior performance of NN controller over conventional PI controller. In addition to this, It is also shown by the resultant response that, the proposed modified vector control structure based on Neural Network controller smoothen out the ripples in the motor torque and stator current as fine as will provide best speed regulation with smaller settling time requirement. DOI: 10.17762/ijritcc2321-8169.150517

Modelling of Neural Network based Speed Controller for Vector Controlled Induction Motor Drive

This project work start with the development of simulation model of rotor magnetic field oriented vector control system based on MATLAB software. This paper proposes the development of a Neural Network controller in place of PI controller commonly used in the vector control structure for efficient speed control and smaller settling time. It is expected that the proposed modified vector control structure based on Neural Network controller smoothen out the ripples in the motor torque and stator current as fine as will provide best speed regulation with smaller settling time requirement. DOI: 10.17762/ijritcc2321-8169.150512

FUZZY OPTIMIZATION FOR SPEED CONTROLLER OF AN INDIRECT VECTOR CONTROLLED INDUCTION MOTOR DRIVE USING MATLAB SIMULINK

The aim of this paper is to investigate the performance of a Fuzzy-Logic-Controller (FLC) which is applied on three-phase induction motor drive system for high-performance industrial applications. In this paper, the FLC is used as a speed controller to replace the conventional PI speed controller. The FLC will determine the time of switching on the Space Vector Pulse Width Modulation (SVPWM) inverter that supplies power to drive the induction motor considering variable direct and quadrature axis inductances. The performance of the suggested technique has been simulated and developed using MATLAB/ SIMULINK for dynamic operating condition, such as certain change in command speed, and step change in load. The simulation result shows the feasibility of the proposed technique in order to improve the speed response and low torque ripple on three phase induction motor drive

A New Induction Motor Adaptive Robust Vector Control based on Backstepping

In this paper, a novel approach to nonlinear control of induction machine, recursive on-line estimation of rotor time constant and load torque are developed. The proposed strategy combines Integrated Backstepping and Indirect Field Oriented Controls. The proposed approach is used to design controllers for the rotor flux and speed, estimate the values of rotor time constant and load torque and track their changes on-line. An open loop estimator is used to estimate the rotor flux. Simulation results are presented which demonstrate the effectiveness of the control technique and on-line estimation

Ugađanje otpora rotora vektorski upravljanog indukcijskog motora korištenjem TS neizrazite logike

In this paper, we focus on the estimation of the rotor resistance to online tune the controllers in case of the Indirect Rotor Field Orientation Control (IRFOC) of Induction Machine (IM). The proposed method is based on the development of an adaptive Takagi-Sugeno (TS) fuzzy flux observer, described in a d-q synchronous rotating frame, to concurrently estimate the IM states and the rotor resistance variation. An investigation of the local pole placement is carried out in order to guarantee both the stability and specified observer dynamic performances. The observer\u27s gains design is based on the resolution of sufficient conditions driven into LMIs terms (Linear Matrix Inequalities). Simulation and experimentation are carried out to show the effectiveness of the proposed results.U ovom radu fokusiramo se na estimaciju otpora rotora za ugađanje parametera kontrolera tijekom rada indukcijskog motora (IM) upravljanog metodom indirektne kontrole orijentacije polja rotora (IRFOC). Predložena metoda je bazirana na razvoju adaptivnog Takagi-Sugeno (TS) neizrazitog obzervera toka, opisanog u d-q sinkronom rotacijskom okviru, kako bi se istovremeno estimirala stanja i varijacije otpora rotora IM-a. Provedeno je istraživanje lokalnog postavljanja polova kako bi se osigurala stabilnost i zadane dinamičke performanse obzervera. Dizajn pojačanja estimatora baziran je na rješenju dovoljnog broja uvjeta izraženih pomoću LMN izraza (linearne matrične nejednakosti). Simulacija i eksperimenti su provedeni kako bi se pokazala ispravnost predloženih rezultata

Development and Implementation of Some Controllers for Performance Enhancement and Effective Utilization of Induction Motor Drive

The technological development in the field of power electronics and DSP technology is rapidly changing the aspect of drive technology. Implementations of advanced control strategies like field oriented control, linearization control, etc. to AC drives with variable voltage, and variable frequency source is possible because of the advent of high modulating frequency PWM inverters. The modeling complexity in the drive system and the subsequent requirement for modern control algorithms are being easily taken care by high computational power, low-cost DSP controllers. The present work is directed to study, design, development, and implementation of various controllers and their comparative evaluations to identify the proper controller for high-performance induction motor (IM) drives. The dynamic modeling for decoupling control of IM is developed by making the flux and torque decoupled. The simulation is carried out in the stationary reference frame with linearized control based on state-space linearization technique. Further, comprehensive and systematic design procedures are derived to tune the PI controllers for both electrical and mechanical subsystems. However, the PI-controller performance is not satisfactory under various disturbances and system uncertainties. Also, precise mathematical model, gain values, and continuous tuning are required for the controller design to obtain high performance. Thus, to overcome these drawbacks, an adapted control strategy based on Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller is developed and implemented in real-time to validate different control strategies. The superiority of the proposed controller is analyzed and is contrasted with the conventional PI controller-based linearized IM drive. The simplified neuro-fuzzy control (NFC) integrates the concept of fuzzy logic and neural network structure like conventional NFC, but it has the advantages of simplicity and improved computational efficiency over conventional NFC as the single input introduced here is an error instead of two inputs error and change in error as in conventional NFC. This structure makes the proposed NFC robust and simple as compared to conventional NFC and thus, can be easily applied to real-time industrial applications. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using feedback linearization of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using proposed simplified NFC as compared to the conventional NFC, rather it shows superior performance over PI-controller-based drive. A hybrid fuel cell (FC) supply system to deliver the power demanded by the feedback linearization (FBL) based IM drive is designed and implemented. The modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) incorporated with the intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burden over conventional NFSMC and thus, suitable for real-time industrial applications. The parameters of the modified NFC is tuned by an adaptive mechanism based on sliding-mode control (SMC). A FC stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the FC during different operating conditions of the drive system. The effectiveness of the proposed method using FC-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated in real-time. It is evident from the results that the system provides optimal dynamic performance in terms of ripples, overshoot, and settling time responses and is robust in terms of parameters variation and external load

A Methodology for Solving the Equations Arising in Nonlinear Parameter Identification Problems: Application to Induction Machines

This dissertation presents a method that can be used to identify the parameters of a class of systems whose regressor models are nonlinear in the parameters. The technique is based on classical elimination theory, and it guarantees that the solution for the parameters which minimize a least-squares criterion can be found in a finite number of steps. The proposed methodology begins with an input-output linear overparameterized model whose parameters are rationally related. After making appropriate substitutions that account for the overparameterization, the problem is transformed into a nonlinear least-squares problem that is not overparameterized. The extrema equations are computed, and a nonlinear transformation is carried out to convert them to polynomial equations in the unknown parameters. It is then show how these polynomial equations can be solved using elimination theory using resultants. The optimization problem reduces to a numerical computation of the roots of a polynomial in a single variable. This nonlinear least-squares method is applied to the identification of the parameters of an induction motor. A major difficulty with the induction motor is that the rotor’s state variables are not available measurements so that the system identification model cannot be made linear in the parameters without overparameterizing the model. Previous work in the literature has avoided this issue by making simplifying assumptions such as a “slowly varying speed”. Here, no such simplifying assumptions are made. This method is implemented online to continuously update the parameter values. Experimental results are presented to verify this method. The application of this nonlinear least-squares method can be extended to many research areas such as the parameter identification for Hammerstein models. In principle, as long as the regressor model is such that the system parameters are rationally related, the proposed method is applicable

Speed Sensorless Induction Motor Drives for Electrical Actuators: Schemes, Trends and Tradeoffs

For a decade, induction motor drive-based electrical actuators have been under investigation as potential replacement for the conventional hydraulic and pneumatic actuators in aircraft. Advantages of electric actuator include lower weight and size, reduced maintenance and operating costs, improved safety due to the elimination of hazardous fluids and high pressure hydraulic and pneumatic actuators, and increased efficiency. Recently, the emphasis of research on induction motor drives has been on sensorless vector control which eliminates flux and speed sensors mounted on the motor. Also, the development of effective speed and flux estimators has allowed good rotor flux-oriented (RFO) performance at all speeds except those close to zero. Sensorless control has improved the motor performance, compared to the Volts/Hertz (or constant flux) controls. This report evaluates documented schemes for speed sensorless drives, and discusses the trends and tradeoffs involved in selecting a particular scheme. These schemes combine the attributes of the direct and indirect field-oriented control (FOC) or use model adaptive reference systems (MRAS) with a speed-dependent current model for flux estimation which tracks the voltage model-based flux estimator. Many factors are important in comparing the effectiveness of a speed sensorless scheme. Among them are the wide speed range capability, motor parameter insensitivity and noise reduction. Although a number of schemes have been proposed for solving the speed estimation, zero-speed FOC with robustness against parameter variations still remains an area of research for speed sensorless control

Field Oriented Controlled Speed Sensorless Control of Induction Motors

In this paper, a special class of adaptive control system, model reference adaptive controller (MRAC) for the speed estimation of the field oriented controlled (FOC) induction motor drive is presented. The proposed MRAC is formed using instantaneous and steady-state values of tuning signal insynchronously rotating reference frame, which is a fictitious quantity and has no physical significance. Requirement of no additional sensors makes the drive suitable for retrofit applications. The proposed MRAC-based speed sensorless field oriented controlled induction motor drive estimation technique has been simulated in MATLAB/SIMULIN