INDIRECT VECTOR CONTROL OF INDUCTIONMOTOR WITH RANDOM LOADING USING ANN

By M.DINESH Reddy (R.No.: 645403)Internal Guide: Sri.T. Reddy ME, (Ph.D)

OVER VIEWIntroduction Vector Control Scalar Control Set backs

Induction motor Modelling

Neural Controller Conventional Controller Set backs

Simulations

Results Conclusion Bibiliography

The simulation of Vector controlled Induction motor is done indirectly by Matlab Simulink.

The Torque - Speed characteristics are similar to dc drive with high starting torque and variable speed.

Vector control decouples Torque and Flux control of IM.

The Indirect Vector control scheme is preferred in the industry because of its simplicity.

The IM is modeled using the d-q transformation as it adequately simulates the transient performance.

The dynamic behavior can be made to match with that of Separately excited dc motor.

INTRODUCTIONOverview

Scalar ControlControls only Magnitude of control variables

System gives Sluggish response due to the coupling effect.

Less effective

High Current transients

System easily prone to instability.

Overview

Vector ControlBoth the Magnitude and Phase alignment of vector variables are controlled.

Decouples the Torque and Flux control of InductionMotor. Vector control gives fast dynamic response without high current transients.

Vector control operation leads to Low energy Consumption,Low operating costs and High efficiency.

Induction motor can be controlled like a separately exited dc motor.

Overview

Fig (a) Separately Excited DC motorFig (b) Vector- Controlled Induction motor.Overview

Principle of Vector Control:

.Frequency as well as the phase are controlled indirectly with the help of the unit vector.

Overview

Direct Vector Control:Direct relies on Flux feedback.

Complex to implement.

High cost.

Measurement is not accurate.Indirect Vector Control:Indirect relies on Speed feedback

Easily to implement.

Low cost.

Accurate response.Overview

rotor pole is directed on de axis

we = wr + wslPhasor diagram of Indirect Vector control :Overview

Field component Iqs should be aligned on the de axis &Torque component of current Ids should be on the qe axis

The total finalized equations :

WhereSlip speedOverview

The voltage equations of induction motor are time varying and complex in nature.A transformation is used which converts stator and rotor variables of induction motor to a frame of reference that rotates at an arbitrary angular velocity. fqd0s =Ks f abcsThe above equation transforms 3 phase variables of stationary circuit elements to arbitrary reference frame.

Three phase stationary reference frame (as-bs cs) variables into two phase stationary reference) frame (ds qs)neglect the Zero sequence component.

Modelling of the Induction MotorOverview

Complete Induction Machine Model:Overview

Synchronously rotating reference frame dynamic model

to represent both ds -qs circuits and dr -qr their variables in a synchronously rotating frame de qe

Dynamic de -qe equivalent circuit of machine qe axis circuit:Overview

Dynamic de - qe equivalent circuit of machine - de axis circuit

Overview

Voltage equations :

Overview

Flux linkages equations:

qse = Lls iqse + Lm(iqse +iqre )

dse = Lls idse + Lm(idse +idre )

qre = Llr iqre + Lm(iqse +iqre )

dre = Llr idre + Lm(idse +idre )

qme = Lm(iqse +iqre )

dme = Lm(idse +idre )

Overview

Dynamic model state equations

dwr / dt = (P/2J)* (Te-TL)Overview

Conventional PI ControllerController: Modify the error signal & achieve better control action.Modify the transient response & the steady state error of the system.The aim of a PI controller is to determine the stator voltage frequency that will make the measured output (speed of the rotor) reach the reference.A proportional (kp) term,which is equal to the product of the error signal by a constant called the proportional gain.

The integral (Ki) term of the controller is used to eliminate small steady errors.The I term calculates a continuous running total of the error signal.Overview

PI Controller:Set backs:

High Peak OvershootProlong SettlingtimeOverview

Neural Proportional Integral Controller:The Neural PI controller is same as the Conventional PI controller but the gain blocks are realised using Neural network techniques.ANN: It is the most generic form of AI for emulating the human thinking process.The basic structure of a Neuron is shown below:Overview

MODEL OF A NEURON A Neuron is the fundamental building block of nervous system that performs computational and communication function.

Overview

Artificial Neural Network :-

It can be defined as a highly connected ensemble of processing elements called neurons or nodes.An artificial neuron is a multi-input, single output processing element consisting of a summation operation and an activation function. Overview

Neural Network SubsystemLayer SubsystemOverview

Neural networks can perform massively parallel operations.Neural networks exhibit fault tolerance since the information is distributed in the connections throughout the network.Self learning capabilityReal time operation.By using Neural PI controller the Peak overshoot is reduced and the system reaches the steady state quickly when compared to a conventional PI controller.

Advantages:Overview

Neural PI ControllerApplications:

Sales ForecastingIndustrial Process control Customer Research Data Validation Risk Management Target Marketing

Overview

SIMULATION RESULTS:

Overview

PARAMETERS:3 PHASE Induction Motor RATING @ 50hp, 460V,4pole,50HzStator resistance [ohm]Stator leakage inductance [H]Rotor resistance [ohm]Rotor leakage inductance [H]Magnetizing inductance [H]Number of poles0.0870.8e-30.2280.8e-334.7e-34Overview

#Case 1: No-LoadPI Controller: Speed(rad/s) Vs Time(s)Overview

Peak Overshoot:5%Torque(N-m) Vs Time(s)Overview

Current (A) Vs Time(s)Overview

At No-Load:NN Controller: Speed(rad/s) Vs Time(s):Overview

Torque(N-m) Vs Time(s)Overview

Current (A) Vs Time(s) Overview

#Case 2: Step Change in -LoadPI Controller: Speed(rad/s)Vs Time(s)Overview

Torque(N-m) Vs Time(s)Overview

Current (A) Vs Time(s)Overview

NN Controller: Speed(rad/s) Vs Time(s):Overview

Torque(N-m)Vs Time(s)Overview

Current (A) Vs Time(s)Overview

#Case 3 : Speed Reversal:PI Controller: Speed(rad/s) Vs Time(s):Overview

Torque(N-m) Vs Time(s) Overview

Current (A) Vs Time(s)Overview

NN Controller: Speed(rad/s) Vs Time(s):

Overview

Torque(N-m)Vs Time(s)Overview

Current (A) Vs Time(s)Overview

ConclusionNeural Controllers are fast acting & more accurate.

Avoids prolonged Settling time & High Peak overshoots.

Future Scope

Implementation of NEuro-Fuzzy CONtroller (NEFCON) for further better performance. NEFCON combines the merits of Fuzzy systems and Neural networks.

Overview

BIBILOGRAPHY

1.C.M.Liaw.Y.S.Kung and M.S.Ouyang Identification and control of inductionmachines using artificial neural networks.IEEE Trans Ind.Applicat. vol.31.pp.612-619,1995.2. C.M.Liaw.Y.S.Kung and C.M.Wu Design and implementation of a high performance field oriented Inductionmotor drive.IEEE Trans Ind.Applicat. vol.38.pp.275-282,1991.3.M.A.Wishart and R.G.Harley Identification and control of inductionmachines using artificial neural networks.IEEE Trans Ind.Applicat. vol.34.pp.412-419,1994.4.Levin and K.S.Narendra Control dynamics systems using neural networks controllability and stabilization. IEEE Trans on Neural networks.NN-1. 1,4-27,1990.5..Artificial neural networks B.Yagna narayana6.An introduction to neural networks JA.Anderson7.Electrical machines P.S.Bimbra8.Electrical machines S.K.Bhatta charya9.Machine modelling Krause10.Electrical drives---- Vedam subramanyam11.Modern power electronics and ac drives-----Bimal.K.BoseOverview

*The aim of a PI controller is to determine the stator voltage frequency that will make the measured output (speed of the rotor) reach the reference.PI stands for Proportional and Integral,two terms which describe two distinct elements of the controller.A proportional term,which is equal to the product of the error signal by a constant called the proportional gain.The proportional term mainly describes the short-term behavior of the controller since it determines how the controller strongly reacts to reference changes.The integral (I) term of the controller is used to eliminate small steady errors.The I term calculates a continuous running total of the error signal.Therefore,a small steady state error accumulates into a large error value over time.this accumulated error signal is multiplied by an I gain factor and becomes the Ioutput of the PI controller

*The neural PI controller is same as the conventional PI controller but the gain blocks are realised using neural network techniques.The basic structure of a neuron is shown below:

Neural networks can perform massively parallel operatiops.Neural networks exhibit fault tolerance since the information is distributed in the connections throughout the network.By using neural PI controller the peak overshoot is reduced and the system reaches the steady state quickly when compared to a conventional PI controller.

The advantages of neural network implementation of the speed controller are as follows:

**ADVANTAGES OF NEURAL PI CONTROLLER*SPEED VS TIME PLOT USING PI CONTROLLER*