Abstract________________________________________________________

The aim of this investigation is to describe the principle of DC motor speed control using

nonlinear armature voltage control. For the armature control mode, the field current is held

constant and an adjustable voltage is applied to the armature. The mathematical model of a

separately excited DC motor (SEDM) with independent armature control can be obtained by

considering the electrical system, electromagnetic interaction and mechanical system.

The armature voltage control of separately excited DC motor can be controlled from below

and up to rated speed using IGBT as a converter. The IGBT firing circuit receives signal

from controller and then chopper gives variable voltage to the armature of the motor for

achieving desired speed. There are two control loops, one for controlling current and another

for speed. The controller used is Proportional type which removes the delay and provides fast

control. Modelling of separately excited DC motor is done. The complete layout of DC drive

mechanism is obtained. The designing of current and speed controller is carried out. After

obtaining the complete model of DC drive system, the model is simulated using

MATLAB(SIMULINK).The simulation of DC motor drive is done and analyzed under

varying speed and varying load torque conditions like rated speed and load torque, half the

rated load torque and speed, step speed and load torque and stair case load torque and speed.

1

CHAPTER 1

INTRODUCTION

2

Chapter 1 Introduction

A DC motor is an electric motor that runs on direct current (DC) electricity. DC motors were

used to run machinery, often eliminating the need for a local steam engine or internal

combustion engine. Today DC motors are still found in applications as small as toys and disk

drives, or in large sizes to operate steel rolling mills and paper machines. Modern DC motors

are nearly always operated in conjunction with power electronic devices. The principle of DC

motor is based on simple electromagnetism. A current-carrying conductor generates a

magnetic field; when this is then placed in an external magnetic field, it will experience a

force proportional to the current in the conductor, and to the strength of the external magnetic

field. The internal configuration of a DC motor is designed to harness the magnetic

interaction between a current-carrying conductor and an external magnetic field to generate

rotational motion. Development of high performance motor drives is very essential for

industrial applications. A high performance motor drive system must have good dynamic

speed command tracking and load regulating response. DC motors provide excellent control

of speed for acceleration and deceleration. The power supply of a DC motor connects

directly to the field of the motor which allows for precise voltage control, and is necessary

for speed and torque control applications. DC drives, because of their simplicity, ease of

application, reliability and favourable cost have long been a backbone of industrial

applications. DC drives are less complex as compared to AC drives system. DC drives are

normally less expensive for low horsepower ratings. DC motors have a long tradition of

being used as adjustable speed machines and a wide range of options have evolved for this

purpose. Cooling blowers and inlet air flanges provide cooling air for a wide speed range at

constant torque. DC regenerative drives are available for applications requiring continuous

regeneration for overhauling loads. AC drives with this capability would be more complex

and expensive. Properly applied brush and maintenance of commutator is minimal. DC

motors are capable of providing starting and accelerating torques in excess of 400% of rated.

D.C motors have long been the primary means of electric traction. They are also used for

mobile equipment such as golf carts, quarry and mining applications. DC motors are

conveniently portable and well fit to special applications, like industrial equipments and

machineries that are not easily run from remote power sources.

3

D.C motor is considered a SISO (Single Input and Single Output) system having

torque/speed characteristics compatible with most mechanical loads. This makes a D.C motor

controllable over a wide range of speeds by proper adjustment of the terminal voltage. Now

days, Induction motors, Brushless D.C motors and Synchronous motors have gained

widespread use in electric traction system. Even then, there is a persistent effort towards

making them behave like dc motors through innovative design and control techniques. Hence

dc motors are always a good option for advanced control algorithm because the theory of dc

motor speed control is extendable to other types of motors as well.

Speed control techniques in separately excited dc motor:

• By varying the armature voltage for below rated speed.

• By varying field flux should to achieve speed above the rated speed.

Different methods for speed control of DC motor:

• Traditionally armature voltage using Rheostatic method for low power dc motors.

• Use of conventional PID controllers.

• Neural Network Controllers.

• Constant power motor field weakening controller based on load-adaptive multi- input

multi- output linearization technique (for high speed regimes).

• Single phase uniform PWM ac-dc buck-boost converter with only one switching

device used for armature voltage control.

• Using NARMA-L2 (Non-linear Auto-regressive Moving Average) controller for the

constant torque region.

Large experiences have been gained in designing trajectory controllers based on self-tuning

and PI control. The PI based speed control has many advantages like fast control, low cost

and simplified structure. This thesis mainly deals with controlling DC motor speed using

IGBT as power converter and PI as speed and current controller.

4

Chapter 1.1 IGBT

Recent technology advances in power electronics have arisen primarily from improvements

in semiconductor power devices, with insulated gate bipolar transistors (IGBT) leading the

market today for medium power applications. IGBTs feature many desirable properties

including a MOS input gate, high switching speed, low conduction voltage drop, high current

carrying capability, and a high degree of robustness. Devices have drawn closer to the 'ideal

switch', with typical voltage ratings of 600 - 1700 volts, on-state voltage of 1.7 - 2.0 volts at

currents of up to 1000 amperes, and switching speeds of 200 - 500 ns. The availability of

IGBTs has lowered the cost of systems and enhanced the number of economically viable

applications. The insulated gate bipolar transistor (IGBT) combines the positive attributes of

BJTs and MOSFETs. BJTs have lower conduction losses in the on-state, especially in

devices with larger blocking voltages, but have longer switching times, especially at turn-off

while MOSFETs can be turned on and off much faster, but their on-state conduction losses

are larger, especially in devices rated for higher blocking voltages. Hence, IGBTs have lower

on-state voltage drop with high blocking voltage capabilities in addition to fast switching

speeds. IGBTs have a vertical structure as shown in Fig. 1.1. This structure is quite similar to

that of the vertical diffused MOSFET except for the presence of the p+ layer that forms the

drain of the IGBT. This layer forms a p-n junction (labelled J1 in the figure), which injects

minority carriers into what would appear to be the drain drift region of the vertical MOSFET.

The gate and source of the IGBT are laid out in an inter-digitised geometry similar to that

used for the vertical MOSFET.

Figure 1.1: Physical Structure of IGBT

5

1.1.1 IGBT Switching Characteristics

One of the main important performance features of any semiconductor switching device is its

switching characteristics. Understanding the device switching characteristics greatly

improves its utilization in the various applications. The main performance switching

characteristics of power semiconductor switching devices are the turn-on and turn-off

switching transients in addition to the safe operating area (SOA) of the device.

1.1.1.1 Turn On Characteristics

The turn-on switching transient of an IGBT with an inductive load is shown in Fig. 1.2. The

turn-on switching transients of IGBTs are very similar to MOSFETs since the IGBT is

essentially acting as a MOSFET during most of the turn-on interval. With gate voltage

applied across the gate to emitter terminals of the IGBT, the gate to emitter voltage rises up

in an exponential fashion from zero to VGE(th) due to the circuit gate resistance (RG) and

the gate to emitter capacitance (Cge).

6

Figure 1.2: IGBT Turn On Characteristics

The Miller effect capacitance (Cgc) effect is very small due to the high voltage across the

device terminals. Beyond VGE(th), the gate to emitter voltage continues to rise as before and

the drain current begins to increase linearly as shown above. Due to the clamp diode, the

collector to emitter voltage remains at Vdc as the IGBT current is less than Io. Once the IGBT

is carrying the full load current but is still in the active region, the gate to emitter voltage

becomes temporarily clamped to VGE,Io, which is the voltage required to maintain the IGBT

current at Io. At this stage, the collector to emitter voltage starts decreasing in two distinctive

intervals tfv1 and tfv2. The first time interval corresponds to the traverse through the active

region while the second time interval corresponds to the completion of the transient in the

ohmic region.

1.1.1.2 Turn on Switching Transients

7

The turn-off switching transients of an IGBT with an inductive load are shown in Fig. 1.3.

When a negative gate signal is applied across the gate to emitter junction, the gate to emitter

voltage starts decreasing in a linear fashion. Once the gate to emitter voltage drops below the

threshold voltage (VGE(th)), the collector to emitter voltage starts increasing linearly. The

IGBT current remains constant during this mode since the clamp diode is off. When the

collector to emitter voltage reaches the dc input voltage, the clamp diode starts conducting

and the IGBT current falls down linearly. The rapid drop in the IGBT current occurs during

the time interval tfi1, which corresponds, to the turn-off of the MOSFET part of the IGBT

(Fig. 1.3). The tailing of the collector current during the second interval tfi2 is due to the

stored charge in the n- drift region of the device. This is because the MOSFET is off and

there is no reverse voltage applied to the IGBT terminals that could generate a negative drain

current so as to remove the stored charge. The only way for stored charge removal is by

recombination within the n- drift region. Since it is desirable that the excess carriers lifetime

be large to reduce the on-state voltage drop, the duration of the tail current becomes long.

This will result in additional switching losses within the device. This time increases also with

temperature similar to the tailing effect in BJTs. Hence, a trade off between the on-state

voltage drop and faster turn-off times must be made.

8

Figure 1.3: Turn Off Transients of IGBT

1.1.1.3 IGBT Safe Operating Area

The safe operating area (SOA) of a power semiconductor device is a graphical representation

of the maximum operational voltage and current limits (i-v) of the device subjected to

various constraints. The forward bias safe operating area (FBSOA) and the reverse bias safe

operating area (RBSOA) represent the device SOA with the gate emitter junction forward

biased or reverse biased, respectively. The IGBT has robust SOA during both turn-on and

turn off. The FBSOA, shown in Fig. 1.4(a), is square for short switching times, similar to that

of power MOSFETs. The IGBT is thermally limited for longer switching times as shown in

the FBSOA figure. The RBSOA of IGBTs, shown in Fig. 1.4(b), is different than the

FBSOA. The upper half corner of the RBSOA is progressively cut out which reduces the

RBSOA as the rate of change of the collector to emitter voltage across the device, dVce/dt, is

9

increased. The RBSOA is reduced as the dVce/dt is increased to avoid latch up within the

device. This condition exists when higher values of dVce/dt are applied may give to the rise

to a pulse of forward decaying current in the body region of the device that acts as a pulse of

gate current that can turn on the device. Fortunately, the dVce/dt values that would cause

latch up in IGBTs are much higher compared to other devices.

(a) (b)

Figure 1.4: (a) FBSOA (b) RBSOA of IGBT

1.1.1.4 IGBT Gate Drive Equipments

IGBTs are voltage controlled devices and require gate voltage to establish collector-to-

emitter conduction. Recommended gate drive circuitry includes substantial ion and off

biasing as shown in Figure 1.5.

Figure 1.5: Typical gate drive circuitry

10

Due to the large input gate-to-emitter capacitance of IGBTs, MOSFET drive techniques can

be used. However, the off biasing needs to be stronger. A +15 V positive gate drive is

normally recommended to guarantee full saturation and limit short circuit current. A negative

voltage bias is used to improve the IGBT immunity to collector-to-emitter dv/dt injected

noise and reduce turn-off losses as shown in Fig. 1.6.

Fig. 1.6: Effect of negative bias on turn off losses

The value of the gate resistance has a significant impact on the dynamic performance of

IGBTs. A smaller gate resistance charges and discharges the IGBT input capacitance faster

reducing switching times and switching losses and improving immunity to dv/dt turn-on (Fig.

1.7). However, a small gate resistance can lead to oscillations between the IGBT input

capacitance and the parasitic lead inductance.

11

Figure 1.7: The IGBT switching losses as a function of gate resistance, RG

The minimum peak current capability of the gate drive power supply and the average power

required are given by,

IG(pk)= ±

Pavg = VGE . QG. fs

where,

DVGE = VGE_on + |VGE_off|

QG = total gate charge (per manufacturer. spec.)

fs = switching frequency

12

Figure 1.8: Total IGBT Gate Charge during switching

In many applications, the gate drive circuitry needs to be isolated from the control circuit to

provide the level shifting and improve noise immunity. The isolation requirements can be

met by using pulse gate transformers (Fig. 1.9) or optical isolation.

Figure 1.9: Typical Bipolar IGBT gate drive using gate pulse transformers

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In bipolar applications, separate turn-on and turn-off gate resistors are used to prevent cross

conduction of an IGBT pair (Fig. 1.10). With opto-isolation, an isolated power supply is

required to provide the gate power to the IGBT.

Figure 1.10: Typical opto-isolation gate drive

Gate drive Layout Considerations

1. Minimize parasitic inductance between the driver output stage and the IGBT (minimizing

the loop area)

2. Minimize noise coupling via proper shielding techniques

3. Utilize gate clamp protections (TVS) to minimize over voltage across gate terminals

4. Utilize twisted pairs, preferably shielded, for indirect connection between the driver and

the IGBT

5. With OPTO coupling isolation, a minimum of 10,000 V/ms transient immunity must be

provided (in hard switching applications)

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Chapter 1.2 Separately Excited DC Motor

1.2.1 Basics of Separately Excited DC Motor

Figure 1.11: Separately Excited DC Motor

• Separately Excited DC motor has field and armature winding with separate supply.

• The field windings of the dc motor are used to excite the field flux.

• Current in armature circuit is supplied to the rotor via brush and commutator segment for

the mechanical work.

• The rotor torque is produced by interaction of field flux and armature current.

1.2.2 Working of Separately Excited DC Motor

• When a separately excited dc motor is excited by a field current of if and an armature

current of ia flows in the circuit, the motor develops a back EMF and a torque to balance the

load torque at a particular speed.

• The field current if is independent of the armature current ia. Each winding is supplied

separately. Any change in the armature current has no effect on the field current.

• The if is generally much less than the ia.

1.2.3 Field and Armature Equation

Instantaneous field current:

15

Where Rf and If are the field resistor and inductor respectively.

Instantaneous armature current:

where Ra and La are armature resistor and inductor respectively.

The motor back emf which is also known as speed voltage is expressed as

Kv is the motor voltage constant.

1.2.4 Basic Torque Equation

1.2.5 Steady State Torque and Speed

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1.2.6 Variable Speed Operation

Figure 1.12: Torque vs Speed Characteristics for different Armature Voltage

• Family of steady state torque speed curves for a range of armature voltage can be drawn as

above.

• The speed of DC motor can simply be set by applying the correct voltage.

• The speed variation from no load to full load (rated) can be quite small. It depends on the

armature resistance.

17

Figure 1.13: Typical operating Region of Separately Excited DC Motor

18

CHAPTER 2

OBJECTIVE

19

Chapter 2 Objective

• Objective of my work during my dissertation is to design a dc motor whose speed can

be controlled up to desired level and armature current increase gradually at the

starting of dc motor and becomes constant very soon.

• I have used two controlling methods; one is current control and other one is speed

control.

• For the current control mechanism armature current controlled algorithm of dc motor

is used in my work. The output current is controlled by a proportional controller in

the feedback which is fed back to IGBT to control the speed.

• IGBT is a fast switching device used in medium power applications.

• Dc motor should gain the speed at once in the starting and later on keeping that at

constant level whereas armature current should increase gradually ,so that motor

doesn’t burn and then it decreases suddenly after motor gains highest speed and

current decreases after that.

• The tool used in my work is MATLAB simulink power toolbox.

20

CHAPTER 3

LITERATURE SURVEY

21

Chapter 3 Literature Survey

Sarat Kumar Sahoo, Ashwin Kumar Sahoo and Razia Sultana in their paper “LabVIEW Based Speed Control of DC Motor using Modulus Hugging Approach” published in ‘European Journal of Scientific Research’ in 2012 described the speed control of separately excited DC motors by PI and PID controller is widely used in industry. A design of controller by applying a several method in analyzing controlled parameter to tune parameter in order to obtain the best process response. A design of PI and PID controller by Modulus Hugging Approach are presented in this paper for testing the performance of controllers in command following control and in disturbance rejection control. From simulation results with LABVIEW, it was found that the controller was fast response and stable, and the effect of disturbance is fast rejected [1].

Awwad A. , Abu-Rub H.,Toliyat H.A. used neural network algorithm for the speed control of ac motors. Tracking of the rotor speed is realized by adjusting the new weights of the network depending on the difference between the actual speed and the commanded speed. The controller is adaptive and is based on a nonlinear autoregressive moving average (NARMA-L2) algorithm. A comparative study between the proposed controllers and the conventional PI one will be presented and the advantages of the proposed solution over the conventional one will be shown. The rotor speed tracks the commanded one smoothly and rapidly, without overshoot and with very negligible steady state error. Computer simulation results are carried out to prove the claims [2]. The project devloped by Nurula Izzati is focused on speed control of DC motor. The main objective is to design and develop GUI software for speed control experiment, where PID controllers’ design approaches has been applied. The controllers have been designed and the system is simulated using MATLAB to analyze their initial performance. The computer is connected to DC Motor via data acquisition card (DAQ Card) and Visual Basic is used to conduct the experiment. Field-testing is implemented to compare the results between the original and modified system with the PID controller. Finally, the performance of the system is analyzed and validation is done in terms of time response, robustness and percentage of error [3].

Theo J.A. de Vries, Member, IEEE in 1998 published in his paper about the design and realization of an on-line learning motion controller for a linear motor is presented, and its usefulness is evaluated. The controller consists of two components: 1) a model based feedback component and 2) a learning feed forward component. The feedback component is designed on basis of a simple second order linear model, which is known to have structural errors. In the design, emphasis is placed on robustness. The learning feed forward component is a neural-network-based controller, comprised of one hidden- layer structure with second-order B-spline basis functions. Simulations and experimental evaluations show that, with little effort, a high-performance motion system can be obtained with this approach [4].

22

C.U. Ogbuka published his paper in 2009 describing the control strategies, transfer functions, and performance analysis of Open Loop Control, Closed Loop Speed Control, and Inner Current Loop Controlled Separately Excited DC Motor are presented both for steady state and dynamic responses. For the Closed Loop Speed Control, three controllers are used, namely: Proportional, Integral, and Proportional-Integral Controllers. In the case of the Inner Current Loop Control, Proportional and Proportional-Integral Controllers are used for analysis. The results obtained show that the Open Loop Control gives a sluggish response which is improved in the Closed Loop Speed Control. The fastest response is obtained in the Inner Current Loop Control and this fast response and ease of control gives the DC Motor a competitive edge over the AC Motors [5].

Abhari S. published paper named ” Optimal control based feedback linearization for position control of DC motor”. This paper proposes the position control of DC motor. Two methods are used for position control, LQR method and feedback linearization. We show that these methods without load torque are stable, but, when load is added to the motor's shaft, LQR and feedback linearization could not make efficient input signal for reference tracking in output. To solve this problem, we combined these methods and will show by using combined method, the position of shaft tracks reference in presence of large torque. For validation of new controller, we compared response with LQR and feedback linearization. Simulation results show stable response of new method [6].

Fei Zhang verified the switching speed of IGBT. An insulated gate bipolar transistor with a novel buffer is proposed and verified by two-dimensional (2D) mixed device-circuit simulations. The structure of the proposed device is almost identical with that of the conventional IGBT, except for the buffer layer which is formed by employing a three-step, gradually changing doping n+ structure. Compared with the conventional IGBT, the proposed device exhibits better trade-off relation between the conduction and switching losses. The turn-off time is halved from 9.4 μs of the conventional IGBT to 4.5 μs of the proposed device, so the operation speed of the proposed device is greatly improved. Further, the forward blocking voltage is enormously increased from 907 V of the proposed device to 1278 V of the proposed device, which is required for high power operation [7].

Thepsatorn P. in his paper presents implement in speed control of a separately excited DC motor using fuzzy logic control (FLC) based on LabVIEW (Laboratory Virtual Instrument Engineering Workbench) program. LabVIEW, is a graphical programming environment suited for high-level or system-level design. Therefore, the principle that are data flow model, different from text-base programming and a sequential model. The user-friendly interface and toolbox design are shown the high level of suitableness and stability of LabVIEW and fuzzy logic on speed control of DC motor. The fuzzy logic controller designed to applies the required control voltage that sent to DC motor based on fuzzy rule base of motor speed error (e) and change of speed error (ce). The results show the control as a FLC that do the comparison with PI and PID controller [8].

23

Jong-Bae Lee , Tae-Bin Im, Ha-Kyong Sung, Young-Ouk Kim published a paper named ” A low cost speed control system of brushless DC motor using fuzzy logic” in 1999.This paper focuses on a low-cost speed control system using a fuzzy logic controller for a brushless DC motor. In digital control of a brushless DC motor, the control accuracy is of a high level, and it has a fast response time. We used a Hall IC signal for the permanent magnet rotor position and for the speed feedback signals, and also for a microcontroller of 8-bit type (80CL580); furthermore, we designed the fuzzy logic controller and implemented the speed control system of the brushless DC motor. To acquire an accurate fuzzy logic control algorithm, a simulation with the MATLAB program has been made, while the performance of the system, found by an experiment for a unit step response, was also verified [9].

Robert Babuˇska and Stefano Stramigioli demonstrated the use of MATLAB and Simulink for modeling, analysis and control design with the help of two examples, a DC motor and a magnetic levitation system. It is assumed that the reader already has basic knowledge of MATLAB and Simulink. The main focus is on the use of the Control System Toolbox functions [10].

In IEEE transaction in 1999 use of fuzzy control is demonstrated. During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the realm of industrial processes, which do not lend themselves to control by conventional methods because of a lack of quantitative data regarding the input-output relations. Fuzzy control is based on fuzzy logic-a logical system that is much closer in spirit to human thinking and natural language than traditional logical systems. The fuzzy logic controller (FLC) based on fuzzy logic provides a means of converting a linguistic control strategy based on expert knowledge into an automatic control strategy. A survey of the FLC is presented; a general methodology for constructing an FLC and assessing its performance is described; and problems that need further research are pointed out. In particular, the exposition includes a discussion of fuzzification and defuzzification strategies, the derivation of the database and fuzzy control rules, the definition of fuzzy implication, and an analysis of fuzzy reasoning mechanisms [11].

P. K. Nandam, and P. C. Sen presented a comparative study of proportional-integral (P-I) and integral-proportional (I-P) control schemes for a dc drive. Various characteristics, such as error signal processing and sensitivity to controller gains, of both the schemes are analysed. The response of both the controllers for a change in speed reference and load torque is discussed. The current response during starting is also presented. It is shown that the I-P scheme offers some distinctive advantages. Experimental and simulation results are also presented.A one quadrant GTO chopper is used as the power conditioning unit in the experimental set-up using a separately excited dc motor [12].

C. Canudas de Wit in 1984 surveyed the control of machines by friction. While considerable progress has been made in friction compensation, this is, apparently, the first survey on the topic. In particular, it is the first to bring to the attention of the controls community the important contributions from the tribology, lubrication and physics

24

literatures. By uniting these results with those of the controls community, a set of models and tools for friction compensation is provided which will be of value to both research and application engineers. The successful design and analysis of friction compensators depends heavily upon the quality of the friction model used, and the suitability of the analysis technique employed. Consequently, this survey first describes models of machine friction, followed by a discussion of relevant analysis techniques and concludes with a survey of friction compensation methods reported in the literature. An overview of techniques used by practising engineers and a bibliography of 280 papers is included [13].

J.Y. Hung and Z. Ding described a method to design an improved motor excitation for three-phase brushless permanent magnet motors is presented. The unique motor excitation reduces ripple in the developed torque, reduces the effects of cogging or detent torque, and is also a minimum average power excitation. Practical benefits are reduced vibration and acoustic noise in speed control applications, and improved accuracy in position control applications. First, an analysis of torque ripple is presented using the exponential Fourier series in the torque model. The analysis is simple, yet extends some well known results by predicting the presence of additional harmonic components. Next, the design of an optimal weighting of stator current harmonics is cast as a type of constrained minimization problem. In contrast to iterative approaches that have been reported in the past, the new design method determines the current harmonic weights in closed form. Steps in the design procedure are demonstrated using measured back EMF data from a 2 hp brushless DC motor [14].

Martina Malkova presented a paper named ”D.C. motor speed control” in Electrical systems & control.In this, a d.c. motor speed control is constructed, where a variable voltage supply is used to feed the field windings. Since the field circuit requires much less power than the armature, this scheme has the advantage that only a small and inexpensive variable voltage supply is required. A disadvantage is that a speed feedback signal is required in order to make speed proportional to input field voltage [15].

Manafeddin Namazov and Onur Basturk (2010) presents the design of a fuzzy control system to control the position of a DC motor. The motor was modelled and converted to a subsystem in Simulink. First, a crisp proportional-derivative (PD) controller was designed and tuned using a Simulink block instead of conventional tuning methods such as hand-tuning or Ziegler-Nichols frequency response method. Then a fuzzy proportional-derivative (FPD) controller was designed and system responses of FPDs with different defuzzification methods were investigated. A disturbance signal was also applied to the input of the control system. FPD controller succeeded to reject the disturbance signal without further tuning of the parameters whereby crisp PD controller failed [16].

The proportional-integral (PI) control is the most used algorithm to regulate the armature current and speed of cascade control system in motor drives. However, even when a tuning design to satisfy some

25

desired performance, the output overshoot is of higher values .In this paper Ibrahim K. Al-Abbas, Rateb Issa told that PI current controller is replaced by proportional-integral-derivative (PID) controller to eliminate the overshoot in current loop and then the overshoot in speed loop. Methods of computing PID current controller parameters are derived using Internal Model Control as a function of motor parameters. The transfer function of overall closed loop current is used to determine PI speed controller parameters. Simulation results show robustness of the proposed method to reference signal and disturbance signal variations [17].

The speed control of separately excited DC [SEDC] motors by PI and PID controller is widely used in industry. In this paper, Raju Singh, Dr.A.K.Pandey proposed the design of PI speed controller using modulus hugging approach for closed loop speed control of dc motor using chopper is presented. Then the stability of overall transfer system of close loop system is analyzed using this approach. It is shown that how the system is made stable using this approach? Then the stability is checked by using Routh-Hurwitz criteria [18].

K. Ramesh, K. Ayyar, A. Nirmalkumar, G. Gurusamy published a paper on ” Design of Current Controller for Two Quadrant DC Motor Drive by Using Model Order Reduction Technique”in 2010. In this paper, design of current controller for a two quadrant DC motor drive was proposed with the help of model order reduction technique. The calculation of current controller gain with some approximations in the conventional design process is replaced by proposed model order reduction method. The model order reduction technique proposed in this paper gives the better controller gain value for the DC motor drive. The proposed model order reduction method is a mixed method, where the numerator polynomial of reduced order model is obtained by using stability equation method and the denominator polynomial is obtained by using some approximation technique preceded in this paper. The designed controllers responses were simulated with the help of MATLAB to show the validity of the proposed method [19].

According to Fatma GURBUZ in ‘Stability Analysis of a Closed-Loop speed Control for a Pulse Width Modulated DC Motor Drive’, the effect of the variation of amplitude and the chopping period of a PWM signal on the stability of a closed-loop control for a DC motor drive is investigated. First, the entire system is formulated as a Linear Quadratic (LQ) tracker with output feedback. Then, stability analysis for the varying amplitude and the varying chopping period is carried out by the methods of root locus and the Jury test. Finally, stability limits obtained from a root locus and Jury test are checked by the simulation of the system in MATLAB [20].

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Ata SEVINC, an adaptive observer estimating all parameters and load torque is proposed for DC servo motors. The observer uses no direct feedback but the adaptation schemes use current and speed measurements. Both the observer and adaptations are simple to implement for real-time applications. Simulation results are satisfactory for the full adaptive observer. If the observer works in parallel with only load torque and armature resistance adaptations, the results are very good even if very low-quality sensors are used. In this simulation, only a single hall sensor is used as a rotational transducer, which produces a single pulse per revolution, and very high level noise and disturbance are added in order to provide a more realistic simulation [21].

Bose B.K. published a paper on ‘Power electronics and motor drives recent technology advances’ in proceedings of the IEEE International Symposium on Industrial Electronics, IEEE. The aim of this paper is to introduce students to the modelling of brushed dc motor and to use computer simulation as a tool for conducting transient and control studies. Simulation can be very helpful in gaining insights to the dynamic behaviour and interactions that are often not readily apparent from reading theory. Next to having an actual system to experiment on, simulation is often chosen by engineers to study transient and control performance or to test conceptual designs. Presently, there are many control laws available to control the brushed dc motor. The control law of angular velocity depends on the motor parameters. The motor parameters are time varying, especially load torque, hence adaptive control is one of the best control law. In standard adaptive control, instability may be occured in the presence of un modelled dynamics. Robust adaptive control is designed so the stability can be guaranteed [22].

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CHAPTER 4

PROBLEM FORMULATION

28

Chapter 4_ Problem Formulation

The greatest advantage of DC motors may be speed control. Since speed is directly

proportional to armature voltage and inversely proportional to the magnetic flux produced by

the poles, adjusting the armature voltage and/or the field current will change the rotor speed.

The problem encounter when dealing with DC motor is the lag of efficiency and losses. It is

required that once DC motor is set to at a particular speed then it shouldn’t change it speed

because of external parameters. In order to eliminate this problem, controller is introduced to

the system. There are so many types of controller available to control the current in the motor

like proportional control, integral control, derivative control, PID controller. So there is

problem of selecting suitable controller in feedback loop. To understand the errors introduced

in DC motor while controlling speed, basic model of speed control will be studied first.

4.1 Basic Model of DC Motor

The basic principle behind DC motor speed control is that the output speed of DC motor can

be varied by controlling armature voltage for speed below and up to rated speed keeping field

voltage constant. The output speed is compared with the reference speed and error signal is

fed to speed controller. Controller output will vary whenever there is a difference in the

reference speed and the speed feedback. The output of the speed controller is the control

29

voltage Ec that controls the operation duty cycle of (here the converter used is a IGBT)

converter. The converter output give the required Va required to bring motor back to the

desired speed. The Reference speed is provided through a potential divider because the

voltage from potential divider is linearly related to the speed of the DC motor. The output

speed of motor is measured by Tacho-generator and since Tacho voltage will not be perfectly

dc and will have some ripple. So, we require a filter with a gain to bring Tacho output back

to controller level. The basic block diagram for DC motor speed control is show below:

Figure 4.1: Closed Loop System Model for Speed Control of DC Motor

The separately excited dc motor is shown as

Figure 4.2: Separately Excited DC motor

The armature equation is shown below:

Va =Eg+ IaRa+ La (dIa/dt)

The description for the notations used is given below:

1. Va is the armature voltage in volts.

2. Eg is the motor back emf in volts.

3. Ia is the armature current in amperes.

4. Ra is the armature resistance in ohms.

30

5. La is the armature inductance in Henry.

Now the torque equation will be given by:

Td = Jdω/dt +Bω+TL

Where:

1. TL is load torque in Nm.

2. Td is the torque developed in Nm.

3. J is moment of inertia in kg/m².

4. B is friction coefficient of the motor.

5. ω is angular velocity in rad/sec.

Assuming absence (negligible) of friction in rotor of motor, it will yield:

B=0

Therefore, new torque equation will be given by:

Td = Jdω/dt + TL --------- (i)

Taking field flux as Φ and (Back EMF Constant) Kv as K. Equation for back emf of motor

will be:

Eg = K Φ ω --------- (ii)

Also, Td = K Φ Ia --------- (iii)

From motor’s basic armature equation, after taking Laplace Transform on both sides, we will

get: Ia(S) = (Va – Eg)/(Ra + LaS)

Now, taking equation (ii) into consideration, we have:

=> Ia(s) = (Va – KΦω)/ Ra(1+ LaS/Ra )

And, ω(s) = (Td - TL )/JS = (KΦIa - TL ) /JS

Also, The armature time constant will be given by:

(Armature Time Constant) Ta = La/Ra

31

Figure 4.3: Model of Separately Excited DC Motor

After simplifying the above motor model, the overall transfer function will be as given

below:

ω (s) / Va(s) = [KΦ /Ra] /JS(1+TaS) /[ 1 +(K²Φ² /Ra) /JS(1+TaS)]

Further simplifying the above transfer function will yield:

ω(s) /Va(s) = (1 /kΦ) /{ 1 +(k²Φ² /Ra) /JS(1+TaS)} ---------------- (iv)

Assuming, Tm = JRa / (kΦ) ² as electromechanical time constant [1]. Then the above

transfer function can be written as below:

ω(s)/Va(s) = (1/kΦ)/ [STm (1+STa)+1] --------(v)

Let us assume that during starting of motor, load torque TL = 0 and applying full voltage Va

Also assuming negligible armature inductance, the basic armature equation can be written as:

Va = KΦω(t) + IaRa

At the same time Torque equation will be:

Td = Jdω/dt = KΦIa ----- (vi)

Putting the value of Ia in above armature equation:

Va=KΦω(t)+(Jdω/dt)Ra/ KΦ

Dividing on both sides by KΦ,

Va/KΦ=ω(t)+JRa(dω/dt)/(KΦ)² ------------------------(vii)

Va/KΦ is the value of motor speed under no load condition.

Therefore,

ω(no load)=ω(t)+JRa(dω/dt)/(KΦ)² = ω (t) + Tm (dω/dt)

Where, KΦ = Km(say) And, Tm=JRa/(KΦ)²=JRa/(Km)²

32

Therefore, J = Tm (Km) ²/ Ra --------- (viii)

From motor torque equation, we have:

ω(s) = KmIa(s)/JS - TL/JS -------- (ix)

From equation (viii) and (ix), we have:

Now, Replacing KΦ by Km in equation (v), we will get:

ω(s)/Va(s)=(1/Km) / (1+STm+S²TaTm) ------------ (x)

Since, the armature time constant Ta is much less than the electromechanical time constant

Tm, (Ta << Tm)

Simplifying, 1 + STm + S²TaTm ≈ 1 + S (Ta+Tm) + S²TaTm = (1 + STm)(1 + STa)

The largest time constant will play main role in delaying the system when the transfer

function is in time constant form. To compensate that delay due to largest time constant we

can use PI controller as speed controller. It is because the zero of the PI controller can be

chosen in such a way that this large delay can be cancelled. In Control system term a time

delay generally corresponds to a lag and zero means a lead, so the PI controller will try to

compensate the whole system . Hence, the equation can be written as:

ω(s)/Va(s) = (1/Km)/((1 + STm)(1 + STa)) -----(xi)

Tm and Ta are the time constants of the above system transfer function which will determine

the response of the system. Hence the dc motor can be replaced by the transfer function

obtained in equation (xi) in the DC drive model shown earlier.

4.2 Deciding the Type Of current Controller

The control action can be imagined at first sight as something simple like if the error speed is

negative, then multiply it by some scale factor generally known as gain and set the output

drive to the desired level. But this approach is only partially successful due to the following

reason: if the motor is at the set-point speed under no load there is no error speed so the

motor free runs. If a load is applied, the motor slows down and a positive error speed is

33

observed. Then the output increases by a proportional amount to try and restore the desired

speed. However, when the motor speed recovers, the error reduces drastically and so does the

drive level. The result is that the motor speed will stabilize at a speed below the set-point

speed at which the load is balanced by the product of error speed and the gain. This basic

technique discussed above is known as "proportional control" and it has limited use as it

can never force the motor to run exactly at the set-point speed.

4.2.1 Importance of Current Controller

When the machine is made to run from zero speed to a high speed then motor has to go to

specified speed. But due to electromechanical time constant motor will take some time to

speed up. But the speed controller used for controlling speed acts very fast. Speed feedback

is zero initially. So this will result in full controller output Ec and hence converter will give

maximum voltage. So a very large current flow at starting time because back Emf is zero at

that time which sometime exceeds the motor maximum current limit and can damage the

motor windings. Hence there is a need to control current in motor armature. To solve the

above problem we can employ a current controller which will take care of motor rated

current limit. The applied voltage Va will now not dependent on the speed error only but also

on the current error. We should ensure that Va is applied in such a way that machine during

positive and negative torque, does not draw more than the rated current. So, an inner current

loop hence current controller is required.

34

CHAPTER 5

PROPOSED WORK

35

Chapter 5 Proposed Work and Implementation

In my work armature controlled algorithm is used to control the speed of DC motor. To

control the speed of DC motor the current is feedback with proportional feedback algorithm.

The difference between the reference current and feedback current is error and that is given

further to speed control devices. In our work IGBT is selected as the speed controlling device

because it is having properties of MOS input gate, high switching speed, low conduction

voltage drop, high current carrying capability, and a high degree of robustness. The designing

of speed control controller in our work can be modelled as:

Figure 5.1: Block Model of Speed Control Design

Now, converting the block model in transfer function, we will get:

36

ω(s)/ω(s)(ref.)= (Kn/K2)(Ra/KmTmTn)(1+TnS/(1+2T2S)S²)/{1+(KnRa/K2KmTmTn)

(1+TnS/(1+2T2S)S²)(K1/(1+T1S))} -------- (xviii)

Here, we have the option to Tn such that it cancels the largest time constant of the transfer

function. So,

Hence, equation --- (xviii) will be written as: ω(s)/ω(s)(ref.)=(KnRa/K2KmTmTn)

(1+T1S)/{K2KmTnS2(1+T1S)+KnRaK1}

Ideally, ω(s) =1/S (S²+αs+β)

The damping constant is zero in above transfer function because of absence of S term, which

results in oscillatory and unstable system. To optimize this we must get transfer function

whose gain is close to unity.

37

5.1 Simulink Model

In our work Matlab Simulink model’s Simpower system is primarily used. Figure 6.1 shows the armature controlled DC motor. By varying torque and moment of inertia, speed of DC motor is controlled.

Figure5.2: Block diagram representing input and output parameters of DC motor

w

Discrete,Ts = 1e-005 s.

powergui

omega,omega ref

100

omega ref

ia

Te

4

TL

Series RLC Branch

Relay

0.05

J

g CE

IGBT

2

Gain

73.24

Display1

73.24

Display

Diode

TL

J

w

ia

Te

A+ A-

DC Motor

DC Source

Figure 5.3: DC motor with Current Control and Speed Control using IGBT

38

Figure 5.3 shows that IGBT is attached in the armature windings. The gate of armature is

operated by the relay output, which provides a saturated output voltage. A feedback loop

using proportional controller is used to correct the deflection in output with reference input

voltage. In designing dc motor all limiting parameters of motor are kept in mind. The model

of motor is further made visible by opening DC motor in figure 5.3. This DC motor model is

shown in figure 5.4.

3

Te

2

ia

1

w

2

A- 1

A+

i +-

iA

TL

Ka

J

f cem

Te

w

Subsystem

Series RLC Branch

71.06

Display1

36.62

Display

s

-+

Controlled Voltage Source

2

J

1

TL

Figure5.4 DC Motor

Further by opening the dc motor subsystem1 coloumb and viscous friction of dc motor comes

in functioning as shown in figure 5.5.

39

wTe

3w2Te

1

fcem

Scope1

Product1Product

0.5

Ke

1s

Integrator

Divide

73.24

Display5

11.26

Display4

36.62

Display3

0.5629

Display2

35.53

Display1

30.97

Display

Coulomb(Tf) &Viscous(Bm*w) Friction

Add

3

J

2

Ka

1

TL

Figure 5.5: Dc motor Subsystem2

In figure 6.2 a power gui block is used. That block provides the environment for the

simulation of power electronics components.

40

CHAPTER 6

RESULTS AND DISCUSSION

41

Chapter 6 Results & Discussion

Results for different gain, moment of inertia and coefficirnt of friction is shown. The table

respresenting and comparing them is as:

Table1: Representing different parameters of DC motor which affect the speed of DC motor

1 Ke 0.5 0.5 0.5 0.52 TL 4 4 7.1 6.93 J 0.05 0.1 0.22 0.224 R 0.5 0.5 0.5 0.55 L 0.01 0.01 0.01 0.016 Coulomb Friction Value 0.1 0.1 0.1 0.1

7 Coeff. Of friction 0.4215 0.415 0.415 0.4158 Gain 2 3.5 11 149 Amplitude of DC Speed 73.24 92.32 91.77 97.33

Figure 6.1 Figure 6.3 Figure 6.5 Figure 6.7

Here figure 6.1 represents the graph between the refrence speed and DC motor speed.

Refrence speed is cosidered to be 100 rpm. As is clear from the figure the speed of dc motor

is 74 rpm whereas it should match the refrence speed. As the value of gain is increased

keeping viscous frictional force of motor constant and a little bit change in moment of inertia

of motor , a more gradual increase in motor speed is obtained along with highest speed of

motor almost kissing the refrence speed. Motor speed is being constant after some seconds of

starting of motor that proves speed of motor is constant now irrespective of any chnages.

This is the speed control of motor.

Figure 6.2 represents the armature current graph. It depicts that armature current suddenly

increases at the start but soon it becomes constant. But figure 6.4 and 6.6 of amrature current

shows that as the moment of inertia and viscous friction of motor is changed, the sudden rise

of armature current becomes smoother and constant after that. This is the required condition

of armature current that first it should gradually gain the highest speed then after motor has

gained its constatnt speed then armatture current should also decrease and remain constant

thereafter.

42

Figure 6.1: Graph between DC motor speed & reference speed

43

Figure 6.2: Graph Showing Variation in Armature Current

Initially the moment of inertia and gain of motor is kept at low value then iot has been found

that the amlitude of DC speed reaches upto 73.24 while refernce speed was 100 rpm. So

results are not satisfactory. Moreover the speed is not constant even aftre a certain time. It is

required in DC motor once required speed is reached, it should remain constant. Above

graphs 6.2 and 6.3 depicts these results.

44

Figure 6.3: Graph between Dc motor speed and reference speed

Figure 6.4: Graph showing Armature Current

45

Figure 6.3 and 6.4 shows the results when moment of inertia of motor and gain of controller

is changed to get the desired results. Still the magnitude of DC motor speed is 92.32 rpm. In

control system theory it has been mentioned that the speed of DC motor can reach up to

maximum 98 rpm, not exactly 100 rpm. So modification as per requirement is done in figure

6.5 and 6.6.

Figure 6.5: Graph between Dc motor speed and reference speed

46

Figure 6.6: Graph showing Armature Current

The graph in figure 6.5 shows that the magnitude of DC motor speed is 91.77. For this the

gain has been increased keeping coefficient of friction constant and moment of inertia 0.22.

Still changes in parameters are required. While the armature current in figure 6.6 satisfies the

required condition that first it should increase suddenly then decrease and then constant

armature current.

47

Figure 6.7: Graph between Dc motor speed and reference speed

Figure 6.8: Graph showing Armature Current

48

To reach up to reference speed gain is increased more upto 14. The DC speed reaches to

97.33 which is approximately the desired value. From table 1 it is cleared that the moment of

inertia causes the constant speed in DC motor. As it is increased more early motor will gain

its constant speed. Figure 6.7 shows that it takes time to reach upto maximum value. This is

because of torque present in motor. Because of this a high armature current doesn’t burn the

motor.

49

Chapter 8 Future work

MATLAB simulation for speed control of separately excited DC motor has been done which

can be implemented in hardware to observe actual feasibility of the approach applied in this

thesis. This technique can be extended to other types of motors. In this thesis, we have done

speed control for rated and below rated speed. So the control for above the rated speed can be

achieved by controlling field flux. The problem of overshoot can be removed using a Neural

Network and Fuzzy approach.

The current in the feedback can be controlled by proportional controller, integral controller,

derivative controller, PID controller. Whereas speed can be varied using IGBT, fuzzy sets,

neurology, or any algorithm different from these can be generated. Using different

combination of current controls and speed varying methods and by comparing them best

suitable method can also be found.

50

REFERENCES

51

[1].Sarat Kumar Sahoo, Ashwin Kumar Sahoo, Razia Sultana,” LabVIEW Based Speed Control of DC Motor using Modulus Hugging Approach” European Journal of Scientific Research ISSN 1450-216X Vol.68 No.3 (2012), pp. 367-376

[2].Awwad A. , Abu-Rub H.,Toliyat H.A. ,” Nonlinear autoregressive moving average (NARMA-L2) controller for advanced ac motor control” Industrial Electronics 2008. IECON 2008.

[3].Nurul Izzati Binti Pandak Jabo,” Speed Control Of DC Motor Using PID Controller Implementation With VISUAL BASIC” November, 2008

[4].Gerco Otten, Theo J.A. de Vries, Member, IEEE, Job van Amerongen, Member, IEEE,” Linear Motor Motion Control Using a Learning Feedforward Controller” IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 2, NO. 3, SEPTEMBER 1997

[5].C.U. Ogbuka,”Performance Characteristics of Controlled Separately Excited DC Motor” The Pacific Journal of Science and Technology Volume 10. Number 1. May 2009 (Spring)

[6].Moradi M. ,Ahmadi, A., Abhari S. ,” Optimal control based feedback linearization for position control of DC motor” Advanced Computer Control (ICACC), 2010 2nd International Conference

[7].Fei Zhang, Lina Shi, Wen Yu, Chengfang Li, Xiaowei Sun,” Novel buffer engineering: A concept for fast switching and low loss operation of planar IGBT”

[8].Thepsatorn P. , Numsomran A., Tipsuwanporn V., Teanthong, T,” DC Motor Speed Control using Fuzzy Logic based on LabVIEW” SICE-ICASE, 2006. International Joint Conference

[9].Jong-Bae Lee , Tae-Bin Im, Ha-Kyong Sung, Young-Ouk Kim ,” A low cost speed control system of brushless DC motor using fuzzy logic” Information, Decision and Control, 1999. IDC 99. Proceedings. 1999

[10]. Robert Babuˇska and Stefano Stramigioli,” Matlab and Simulink for Modeling and Control” November 1999

[11]. IEEE TRANSACTIONS ON SYSTEMS, MAN. ANI) C’YHT.RNT.TI (S VOI. 20, NO. 2. MAR (I/APRII. 1990).

[12]. P. K. Nandam, and P. C. Sen, “A comparative study of proportional-integral (P-I) and integral-proportional (I-P) controllers for dc motor drives,” Int. Jour. of Control, vol. 44, pp. 283-297, 1986.

[13]. B. Armstrong–Hélouvry, P. Dupont and C. Canudas de Wit, “A survey of Models, Analysis Tools and Compensation Methods for the control of Machines with Friction”, Automatica, vol. 30, no. 7, pp. 1083-1138, 1994.

[14]. J.Y. Hung and Z. Ding, “Design of currents to reduce torque ripple in brushless permanent magnet motors”, Proc.Inst. Elect. Eng., vol. 140, pt. B, no. 4, pp. 260–266, July 1993.

[15]. Martina Malkova,” D.C. motor speed control” Electrical systems & control 11.5.2006

[16].Manafeddin Namazov and Onur Basturk (2010) DC motor position control using fuzzy proportional-derivative controllers with different defuzzification methods An Official Journal of Turkish Fuzzy Systems Association Vol.1, No.1, pages 36-54, 2010

52

[17]. Ibrahim K. Al-Abbas, Rateb Issa,” Overshoot Elimination in Cascade Control of Separately Excited DC Motors” European Journal of Scientific Research ISSN 1450-216X Vol.85 No.1 (2012), pp.98-104

[18]. Raju Singh1, Dr.A.K.Pandey2,”Stability Analysis of Closed Loop Speed Control of SEDC Motor Using Routh Hurwitz Criteria” GJCAT, Vol 2 (1), 2012, 926-928 ISSN: 2249-1945

[19]. K. Ramesh, K. Ayyar, A. Nirmalkumar, G. Gurusamy,” Design of Current Controller for Two Quadrant DC Motor Drive by Using Model Order Reduction Technique”, IJCSIS, Vol. 7, No. 1, pp. 17-24, January 2010, USA

[20]. Fatma GURBUZ, Eyup AKPINAR, „Stability Analysis of a Closed-Loop speed Control for a Pulse Width Modulated DC Motor Drive Turk J Elec Engin,‟ VOL.10 No.3 2002.

[21]. Ata SEVINC,” A Full Adaptive Observer for DC Servo Motors”, Turk J Elec Engin, VOL.11, NO.2 2003, c T¨UB_ITAK

[22]. Bose B.K., Power electronics and motor drives recent technology advances, Proceedings of the IEEE International Symposium on Industrial Electronics, IEEE, 2002, pp 22-25.

[23]. Sabat Anwari,” Robust Model Reference Adaptive Control of Angular Velocity Control Simulation of Brushed DC Motor” Jurnal Teknik Elektro Vol. 6, No. 1, Maret 2006: 30 - 36

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