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A Low-cost Four-quadrant Chopper-fed Embedded DCDrive Using Fuzzy ControllerN. Senthil Kumar a , V. Sadasivam b & M. Muruganandam aa Department of Electrical and Electronics Engineering, Mepco Schlenk Engineering College,Sivakasi, Tamilnadu, Indiab Department of Computer Science and Engineering, Manonmaniam Sundaranar University,Tirunleveli, Tamilnadu, IndiaVersion of record first published: 31 May 2007.

To cite this article: N. Senthil Kumar , V. Sadasivam & M. Muruganandam (2007): A Low-cost Four-quadrant Chopper-fedEmbedded DC Drive Using Fuzzy Controller, Electric Power Components and Systems, 35:8, 907-920

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Electric Power Components and Systems, 35:907–920, 2007

Copyright © Taylor & Francis Group, LLC

ISSN: 1532-5008 print/1532-5016 online

DOI: 10.1080/15325000701199388

A Low-cost Four-quadrant Chopper-fed Embedded

DC Drive Using Fuzzy Controller

N. SENTHIL KUMAR

Department of Electrical and Electronics Engineering

Mepco Schlenk Engineering College

Sivakasi, Tamilnadu, India

V. SADASIVAM

Department of Computer Science and Engineering

Manonmaniam Sundaranar University

Tirunleveli, Tamilnadu, India

M. MURUGANANDAM

Department of Electrical and Electronics Engineering

Mepco Schlenk Engineering College

Sivakasi, Tamilnadu, India

Abstract A low-cost fuzzy controller for closed loop control of DC drive fed by

four-quadrant chopper is designed and presented in this article. The fuzzy controlleris implemented in a low-cost 8051 micro-controller based embedded system. The

controller is used to change the duty cycle of the converter; thereby, the voltage fedto the armature of the separately excited motor to regulate the speed. The simulated

closed loop performance of the fuzzy controller in respect of load variation andreference speed change has been reported. Further, the dynamic response of DC

motor with fuzzy controller is tested and found to be satisfactory. As the design ofproposed controller does not depend on any of the motor parameters, it can be used

to control DC drive of any rating by very minor modification in the hardware. Thisadvantage of the proposed system is tested for two different motor parameters.

Keywords DC-DC power conversion, DC motor drives, fuzzy control, micro-controllers

1. Introduction

DC motor drives are highly controllable and are used in many applications such as

Lift, Crane, Robotic manipulators, Traction, etc. High performance servo applications

require the motor drive to follow speed commands with minimal steady state error and

Received 18 April 2006; accepted 3 January 2007.Address correspondence to Prof. N. Kumar, Dept. of Electrical and Electronics Engineer-

ing, Mepco Engineering College Post, Sivakasi, Virudhungar, Tamilnadu, 626 005, India. E-mail:nsk_vnr@mepcoeng.ac.in

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overshoots. Such drive systems must have fast acceleration and deceleration capabilities

so that the desired speed command profile is always followed, even under load torque

disturbances.

Different control strategies have been implemented to regulate the DC-DC converter

and the DC motors including PI, fuzzy logic control, and sliding mode control. Though

general PI and PID controllers are widely used for motor control applications, their

design depends upon motor parameters. So it does not give satisfactory results when

motor parameters, loading conditions, and the motor itself are changed. The fuzzy logic

controller (FLC) can be designed without the exact model of the system [1]. For FLC,

it is sufficient to understand the general behavior of the system. This approach of FLC

design guarantees the robust control even if there is a change in the parameters on the

motor drives [2].

Fuzzy logic has been implemented for motor control applications using different

converters and micro-controllers, and to regulate the output voltage of a DC-to-DC con-

verter [3]. The design of fuzzy controller for a three-phase full wave controlled converter

fed DC motor is implemented in a 16-bit micro-controller [4]. The fuzzy controller for

a DC motor has been simulated in MATLAB environment and proved to outperform PI

control [5]. Fuzzy controller for four-quadrant DC drives without speed sensor [6] and

a micro-controller based fuzzy controller has been designed and implemented for a DC

motor [7].

In this article, the four-quadrant chopper (Class E chopper) controlled by a fuzzy

controller suitable for embedded system implementation is presented. The four-quadrant

converter is designed to have a switching frequency of 14 KHz. The use of high switch-

ing frequency reduces torque ripples on the motor shaft. Such converter requires both

current and voltage reversing capability to match rapidly changing speed references and

compensate for step load disturbances. Two control loops, such as inner ON/OFF current

controller and outer fuzzy controller, are used in the proposed controller. The quadrant

of operation is decided by comparing the reference speed and the actual speed of the

motor.

This article is organized as follows. Section 2 describes the proposed system of

separately excited motor control. Modeling and simulation of DC motor and the four-

quadrant chopper are discussed in Section 3. Section 4 explains the structure of the fuzzy

controller used and its components. The simulation results of the proposed system are

given in Section 5. The embedded system implementation of the proposed controller is

described in Section 6. Section 7 discusses the conclusions made out of the present work.

2. Proposed System

The block diagram of the proposed system is shown in Figure 1. The system consists

of four-quadrant chopper type DC-to-DC converter for driving the separately excited DC

motor. An 8051 based micro-controller with an inbuilt pulse width modulation (PWM)

unit is used to generate the PWM waveform required to switch the DC-to-DC converter.

A tacho generator is used to sense the speed of the motor.

The designed closed loop control has two loops. One is outer speed control loop

and the other one is inner current control loop. The inner current control uses ON/OFF

control and switches off the PWM signal whenever the motor current exceeds the rated

reference current, ILref . This has the advantage of using DC motor with any specification.

The change in ILref can be easily done by hardware using a potentiometer connected to

the comparator unit.

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Chopper Drive Using Fuzzy Controller 909

Figure 1. Block diagram of the proposed system.

In outer speed control loop, the motor speed sensed by the tacho generator is fed

to an analog to digital converter (ADC), which is an inbuilt unit of microcontroller

system. The motor speed is compared with the reference speed. After comparison, error

signal and the change in error are calculated and are given as input to fuzzy controller.

The fuzzy controller attempts to reduce the error to zero by changing the duty cycle

of switching signal. Fuzzy controller used has two inputs and one output, as shown in

Figure 2. The inputs to the fuzzy controller are error and change in error. The output of

the fuzzy controller is the change in duty cycle. The new duty cycle for the converter is

then calculated from the previous duty cycle and the output of the fuzzy controller.

The PWM signal is generated by the microcontroller using the duty cycle calculated.

This PWM signal is applied to a gating circuit. This gate control switches off the PWM

signal, if the output from the comparator is zero. The comparator compares the actual

motor current with the reference current and switches off the PWM signal if the motor

current exceeds the reference current. The output of the gate control switch is now given

to a selector logic, which can select the switches to be controlled based on the quadrant

of operation. The isolator and driver circuit drive the MOSFET switches using the signals

from the selector unit.

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Figure 2. Structure of the fuzzy controller used.

The model of the DC motor and the DC-to-DC converter was developed and simu-

lated using MATLAB simulink toolbox. The fuzzy controller was designed and simulated

by using the MATLAB fuzzy logic toolbox.

3. Modeling and Simulation of DC Motor and Four-quadrant Chopper

3.1. DC Motor

The simulation of the entire set-up was done based on equation model of the motor. The

DC motor has been modeled using Eqs. (1) and (2).

d 2�

dt2D

1

J

�

KT io � Bd�

dt� TL

�

(1)

dio

dtD

1

L

�

�Rio C Vo � Kb

d�

dt

�

(2)

where

J —moment of inertia of the motor,

B—friction coefficient of the motor,

Kt —torque constant of the motor,

Kb—motor back emf constant,

TL—load torque applied,

io—armature current,

Vo—armature voltage applied,

R—armature resistance, and

L—armature inductance.

The simulated model of the DC motor is shown in Figure 3.

3.2. Four-quadrant Chopper

The Class E four-quadrant chopper can be operated in any one of the four quadrants,

as shown in Figure 4. For the first quadrant of operation, the load voltage and current

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Figure 3. Simulink model for the motor.

are positive. So the power is transferred from source to load. In the second quadrant

of operation, the load current is negative and load voltage is positive. The power flows

in reverse direction from load to supply side. In the third quadrant operation, the load

voltage and current are negative. Power flows from DC source to load. For the fourth

quadrant operation, the load voltage is negative and the load current is positive. The

power flows from load to supply.

Thus, the operation of the chopper is used to drive DC motors with forward motoring

in first quadrant, forward braking in second quadrant, reverse motoring in third quadrant,

and reverse braking in fourth quadrant [8, 9].

The chopper output voltage and current during different quadrants of operation are

given in Table 1. Every quadrant of operation will have two modes of conduction switches

and they are also given in the table. The converter output voltage and current were

simulated using proper switching signals applied to the chopper switches.

Figure 4. Four-quadrant chopper.

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Table 1

Chopper switching and quadrant of operation

Conducting switchesChopper output

voltage in

Operating mode

Mode 1

(motoring

or braking)

Mode 2

(free-

wheeling) Mode 1 Mode 2

Chopper

output

current

Forward motoring (I quadrant) Q1, Q4 D2, Q4 Vs 0 Positive

Forward braking (II quadrant) D1, D4 Q2, D4 0 Vs Negative

Reverse motoring (III quadrant) Q3, Q2 D4, Q2 �Vs 0 Negative

Reverse braking (IV quadrant) D3, D2 Q4, D2 0 �Vs Positive

4. Design of Fuzzy Controller

4.1. Fuzzy Logic Control

Fuzzy logic controller is an attractive choice when precise mathematical formulations

are not possible [10]. Fuzzy logic controllers are more robust than other non-linear

controllers and do not need fast processors. Further, they can work with less storage than

the conventional look up table for non-linear controllers.

Fuzzy logic is used in an outer speed control loop. The speed is fed back and

is compared with the reference speed. After comparison, the error and the change in

error are calculated and are given as input to fuzzy controller. In this work, the error

is normalized to per unit value with respect to the reference speed. This helps in using

the fuzzy controller for any reference speed. The fuzzy controller will attempt to reduce

the error to zero by changing duty cycle of switching signal. The general PI, like fuzzy

controller shown in Figure 2, is used in this work [8].

4.2. Sugeno Fuzzy Controller

There are two types of fuzzy controllers, viz., Mamdani and Sugeno type fuzzy con-

trollers. In this work, Sugeno fuzzy controller is used. It uses singleton membership

functions for the output variables. The Sugeno type controller is used because it can be

easily implemented in any embedded system and reduces calculations. Furthermore, the

reduction in calculation can result in real-time operation.

4.3. Fuzzification

In the present work, the error and change in error of speed are fuzzified. Seven linguistic

fuzzy sets with triangular membership function are used, as shown in Figure 5. The seven

sets used for fuzzy variables ‘error’ and ‘change in error’ are negative big (NB), negative

medium (NM), negative small (NS), zero (Z), positive big (PB), positive medium (PM),

and positive small (PS).

4.4. Defuzzification

The reverse of fuzzification is called defuzzification. Weighted average method of de-

fuzzification suitable for Sugeno type controllers is used in this work. The defuzzified

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Figure 5. Fuzzy memberships used.

output is the change in duty cycle. The new duty cycle is calculated by adding the existing

duty cycle and the change in duty cycle calculated after defuzzification.

4.5. Rule Table and Inference Engine

The fuzzy rules used in the design are in the general “If–Then” format. If error is Ai ,

and change in error is Bi , then output is Ci . Here the “if” part of a rule is called the

rule-antecedent and is a description of a process state in terms of a logical combination

of fuzzy linguistic sets. The “then” part of the rule is called the rule consequent and is

a description of the control output in terms of a logical combinations of fuzzy sets. The

designed fuzzy controller increases the change in duty cycle when the error is positive

and decreases the same when the error is negative.

4.6. Quadrant Selection Control

The four-quadrant operation is decided by the reference speed of the motor and the actual

speed at which the motor is running. If the reference speed is changed from positive to

negative or vice versa, then the quadrant control will select the corresponding quadrant.

Here, the positive value of speed is considered for forward direction and negative values

for reverse direction of the motor. The quadrant selection will decide the gating signals

for the switches.

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Table 2

110 V DC motor parameters

DC motor parameters Value

DC supply voltage 110 V

Armature resistance Ra 1 �

Armature inductance La 46 mH

Inertia constant J 0.093 Nm2

Damping constant B 0.008 Nm/rad/s

Torque constant parameter 0.55 Kt

Back emf constant 0.55 Km

Speed 1500 rpm

5. Simulation Results

The fuzzy toolbox is used to test and evaluate the fuzzy controller proposed. The simu-

lation was done for a chopper-fed DC motor with the fuzzy controller. The parameters

of the DC motors used are given in Tables 2 and 3. The computer simulation is done for

a step change in motor reference speed and the actual change in speed is recorded. The

step change in load torque is also applied and the corresponding change in the speed is

recorded.

The simulation is done based on equation modeling technique in MATLAB/simulink

toolbox. The complete model developed is given in Figure 6. The simulated graph of

normalized speed change from C1800 rpm to �1800 rpm in a 220 V motor with rated

load is given in Figure 7. The reference speed is initially 1800 rpm for 5 sec. So the

motor is operated in first quadrant (i.e., forward motoring) for first 5 sec and then the

reference speed is changed to �1800 rpm, and so the braking is applied and the motor

is operated in second quadrant (i.e., forward braking). After the motor speed becomes

zero, the motor is operated in the third quadrant (i.e., reverse motoring).

The simulated graph of normalized speed change from �1800 rpm to C1800 rpm

in a 220 V motor is given in Figure 8. The reference speed is initially �1800 rpm for

5 sec. So the motor is operated in third quadrant (i.e., reverse motoring) and then the

set speed is changed to C1800 rpm. So the braking is applied and the motor is operated

Table 3

220 V DC motor parameters

DC motor parameters Value

DC supply voltage 220 V

Armature resistance Ra 0.6 �

Armature inductance La 0.008 H

Inertia constant J 0.011 Nm2

Damping constant B 0.004 Nm/rad/s

Torque constant parameter 0.55 Kt

Back emf constant 0.55 Km

Speed 1800 rpm

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Figure 6. Simulink model of the proposed system.

Figure 7. Graph of normalized speed variation for the step change in reference speed from C1800

rpm to �1800 rpm with rated load.

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Figure 8. Graph of normalized speed variation for the step change in reference speed from �1800

rpm to C1800 rpm at rated load.

in the fourth quadrant (i.e., reverse braking). After the motor speed becomes zero, the

motor is operated in the first quadrant (i.e., forward motoring).

The simulated results in Figures 9 and 10 show the speed regulation for a step

change in the reference speed and the load applied. The reference speed is changed in

two steps from 0 to 60% of rated speed at 0 sec and then to 100% of rated speed at

3 sec. The load applied to the motor is changed from 0 to 100% at 6 sec. Figure 9 shows

the speed response for 110 V motor with the parameters in Table 2, and Figure 10 shows

the speed response for 220 V motor with the parameters in Table 3. These results show

the effectiveness and the advantage of the proposed fuzzy controller. The same fuzzy

controller works effectively on both 110 V and 220 V motors with the only change in

the reference current given to the inner current controller.

6. Embedded System Implementation

The fuzzy controller was implemented practically using Cygnal 8051 based processor

(C8051F005) and the required software was developed in C language. A four-quadrant

chopper was built with the MOSFET switches. A tacho generator was used to sense the

speed.

The micro controller (C8051F005) has 8051 compatible core with the following

features: 12-bit eight-channel ADC; two 12-bit DACs, two comparators, 2-kB data RAM,

and 32-kB flash memory. It also has an in-built PWM waveform generator available as

a programmable counter array. The PWM is generated at a frequency of 14 kHz. This

PWM waveform is then level amplified and fed to the DC-DC power converter through

IR2110 isolator chip. The chopper output is used to supply the armature of the DC motor

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Figure 9. Graph of normalized speed variation for the step change in the reference speed from 60

to 100% applied at 3 sec and step change in load torque from 0 to 100% applied at 6 sec for an

110 V motor.

Figure 10. Graph of normalized speed variation for the step change in the reference speed from

60 to 100% applied at 3 sec and step change in load torque from 0 to 100% applied at 6 sec for

a 220 V motor.

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Figure 11. Hardware setup used.

whose speed is to be controlled. The tacho-generator connected to the motor shaft gives

a DC voltage proportional to the speed and this DC voltage is fed to the ADC available

in the micro-controller. The photo of hardware setup used is given in Figure 11.

The flowchart of the control software used is given in Figure 12. For testing purposes,

the motor was run initially at half the rated speed and then after about 5 sec to rated

speed. The simulated graph of motor with fuzzy controller is given in Figure 13 and the

experimental graph of motor speed for the similar condition is given in Figure 14. The

experimental graph agrees with the simulated waveforms and confirms the use of FLC

for the control of motors.

7. Conclusion

This article presents the development and implementation of a real-time and low-cost

fuzzy controller for an embedded DC drive system. The fuzzy controller is implemented

in an 8051-based embedded micro-controller system. The advantage of this system is

that it does not require the mathematical model of the system for closed loop control. It

also has the advantage of reduced time for implementation after design. As embedded

system of programming is used, the system has the advantage that it can be easily

reconfigured at any time and reprogrammed according to the end use. Also, it is a low-

cost implementation of the closed loop fuzzy controller.

The fuzzy controller operation was tested for two different motors and was found to

have satisfactory response for both the motors. Thus, it is evident that the fuzzy controller

can be used for any motor with only modification in the reference current setting. The

dynamic response of DC motor speed variation with fuzzy controller was tested with

practical implementation and found to be giving satisfactory results.

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Figure 12. Flowchart of the control algorithm.

Figure 13. Simulated waveform of speed variation for the step change in reference speed.

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Figure 14. Experimental waveform obtained for step change in reference speed.

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