fuzzy pre-compensated pi controller for pmbldc motor drive

8/9/2019 Fuzzy Pre-compensated PI Controller for PMBLDC Motor Drive

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Fuzzy Pre-compensated PI Controller forPMBLDC Motor Drive

- The advanced digitalized control of

DC motor

Seminar presentation by-

PAPANNA DHANANJAY,

M.TECH-POWER ELECTRONICS,

1st SEMESTER, TOCE, EEE

nder The Guidance,r. JAY KUMAR,ENIOR LECTURER,OCE, EEE Dept, VTU.

11


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22Fuzzy Pre-compensated PI

INTRODUCTION:

Fuzzy Pre-compensated PI Controller is the advanced speed

control method forPMBLDC (Permanent Magnet Brushless

Direct Current) Motor Drive which provides precise

mathematical modeling of the system feasibly.

Its most cost competitive and eliminate hardware &

software design complexity in the system.


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AIM:

esign a PMBLDC motor drive that satisfies the following needs:

od dynamic performance with zero steady state error.

curate mathematical model of the drive system for tuning tI gains in order to overcome perturbation and variations ofystem parameters.

duce the hardware & software design complexity.

duce chatter, energy loss, plant damage, and excitation ofnmodelled dynamics.


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Existing System:

PMBLDC MOTOR DRIVECONTROLLERS

Sliding ModeController

PI /PID controller


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PROBLEM STATEMENT:

Fuzzy Pre-compensated PI

nventional PMBLDC motor drive controllers we are facingollowing problems:

terred dynamic performance with zero steady state error.

e variation of the operating point of the system, such asvariation of reference speed, load and the DC linkvoltage which leads to oscillations in the system.

atter, energy loss, plant damage, and excitation ofunmodelled dynamics.


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The Challenge:

To design the universally acceptable PMBLDCmotor drive controller

that satisfies all the aims and overcomes all the problems specified.


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PROPOSED SOLUTION:

Use Fuzzy Logic technique to design the PMBLDC motor drive

controller.


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FUZZY LOGIC:

Fuzzy Logic incorporates a simple, rule-based

IF X AND Y THEN Z

approach to a solving control problem rather than attempting to model a

system mathematically.For example: Let us consider motor speed control

Instead of "SP =500HP

We take "T


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Programming methodology:

"IF (process is too slow) AND (process is getting slower)

THEN (add speed to the process)"

or

"IF (process is too fast) AND (process is speeding rapidly)

THEN (slow the process quickly)

Fuzzy Pre-compensated PI(a) Binary logic (b) Fuzzy logic


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1010 Fuzzy Pre-compensated PI Controllerfor PMBLDC MOTOR

PI CONTROLLER:

PI Controller (proportional-integral controller)

is a feedback controller which drives the plant to be controlled with a

weighted sum of the error.

SP: Set Point

PV: Process Variable

MV: Manipulated Variable


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Advantage of a Proportional Integral

Controller:

PI controller causes the steady-state error to be zerofor a step input.

Disadvantages of a Proportional Plus Integral Controller:PI controller introduces a phase-lag. This means that the phase

margin (a measure of stability) decreases.

So careful design considerations with respect to the gain must be

considered.


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Digital Signal Processing is concerned with the

representation of the signals by a sequence of numbers or

symbols and the processing of these signals. Digital signal processing

and analog signal processing are subfields of signal processing.

DSP includes subfields like: sensor array processing, audio signal

processing, spectral estimation, statistical signal processing, etc.

DSP (Digital Signal Processing):


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1313 Fuzzy Pre-compensated PI Controllerfor PMBLDC MOTORBLOCK DIAGRAM-I:


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1. The Power circuit

2. The controller

q Reference speed

q Rotor speed monitoring

q The speed controller

q Rotor position sensingq Reference current generation

q Winding current sensing

q

The current controllerq Gate drive control unit


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BLOCK DIAGRAM-IIWORKING OF FUZZY PRECOMPENSATED PI SPEED CONTROLLER

The Speed Controller


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I. The Speed Controller

e (n)= w* (n) w(n) ) e (n) => speed error of electric drive.

y(n) = f [e (n), e (n)] w* => reference speed of electric drive

e(n) = e(n)-e(n-1) w => actual speed of electric drive.

w*'= w* + y(n) e (n) => change in error

e'(n) = w*' w y (n) is a compensation term

e' (n) = e' (n) - e' (n-1) (determined on the basis of fuzzy logicTref (n) = Tref (n-1) + mapping function) at an instant n.

Kp e' (n) +Ki e' (n) f [e (n), e (n)] => compensation term

II.

Fuzzy Pre-compensator w*' => compensated reference signalq. Structure of Fuzzy Logic Tref => torque reference

Control


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Fuzzy Process consists of the following five steps:

Fuzzification of input variable:

The process of fuzzification is assigning membership functions forvarious fuzzy subsets (seven fuzzy subsets namely PB, PM, PS,

ZE, NS, NM, NB are considered in this study) on the basis of I/P.

Application of Fuzzy operator (AND, OR, NOT ) in theIF part of the rule.

IF e (n) is negative big (NB) AND e (n-1) is positive big (PB)

IF is negative big (NB) AND is Zero (ZE)

Fuzzy Pre-compensated PI Controllerfor PMBLDC MOTOR


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3. Implication from the antecedent to the consequent (THEN

part of the rule)

THEN u is Zero (ZE).THEN u is "negative medium (NM)".

4. Aggregation of the consequent across the rules.

With the seven fuzzy subsets forty-nine rules are writtenThese rules are given in Table-2.

For example: IF =+1 AND =-2 THEN u =-1


TABLE II


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TABLE-II

Inference: The inference is the process of determining the degree of

belonging of the output (u) to the various fuzzy subsets,

for given values of and .

Th d f b l i f () d h i () t f


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Fuzzy Pre-compensated PIController for

2121

The degree of belonging of error () and change in error () to fuzzy

subsets is shown in Table. The degree of belonging for output (u) is als

calculated in this table.

TABLE: Inference

DEFUZZIFICATION


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4. DEFUZZIFICATION:

Defuzzification is the process of obtaining crisp output from

the output of the interference and fuzzy subsets. To obtain u,

the following equation is used-

Where,u=> output fuzzy setAi => output fuzzy subsetai => degree of belonging (output of interference)

Example:u= -2*0.18-1*0.42-1*0.12-1*0.28 = 1.180.18+0.42+0.12+0.28


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Basic structure of fuzzy logic control:

Fuzzy membership function


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The different output fuzzy sets:

output negative, output zero,output positive

The input fuzzy sets havingPositive and negative error

DSP B d I l t ti f th D i S t


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DSP Based Implementation of the Drive System:

Finally the assembly language software is developed for closed loop

speed control of the PMBLDC drive system with Fuzzy

Pre-compensated PI speed

Controller technique.

Here TMS320F240 DSP

microchip is used.

RESULTS AND DISCUSSION


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RESULTS AND DISCUSSION:

(PI speed controller) (Fuzzy pre-compensated PI controller)Scale: 300 rpm /div (channel 1 and 2), 4 A/div (channel 3 and 4)

100-ms/ div. (time scale)Figure: Starting response of the PMBLDC motor drive.Let the drive speed be 500rpm (reference speed). starting response ofFuzzy precompensated PI speed controller the starting time is 20 msecless than the PI speed controller.



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(PI speed controller) (Fuzzy pre-compensated PI controller)Scale: 300 rpm /div (channel 1 and 2), 4 A/div (channel 3 and 4)

100-ms/ div. (time scale)

Figure: Speed reversal response of the PMBLDC motor drive.

Let the drive speed be -500rpm (reference speed). Reversal response

time is 700 ms with fuzzy precompensated PI and 900 ms with PI speed

controllers. Hence, there is reduction in reversal time by 200 ms.


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SUMMARY OFWORK

In case of permanent magnet motor, Fuzzy logic controlapparently offers a possibility of obtaining an improvement in thequality of the speed response, compared to PI control.

Fuzzy logic provides Accurate mathematical model ofthe drive system for tuning the PI gains in order toovercome perturbation and variations of systemparameters.


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Finally, I Thank to novel fuzzy logic method

That as boosted the performance of the control system in

electric drives.


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Q/A

Questions and answer time


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3131 Fuzzy Pre-compensated PI Controller

THANK YOU

fuzzy pre-compensated pi controller for pmbldc motor drive

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