Thursday, April 30, 2009

Tuning Servo Motor

Introduction
To paraphrase an adage, there are two types of motion
control engineers, those that are comfortable tuning a
servo loop, and those that aren’t. And if you are one of
those engineers that aren’t comfortable, you in turn, have two
options. The first is to use a non-servo device such as a step motor,
and the second is to get comfortable!
Whether you are a relative novice, or an experienced hand with
servo tuning, this article will help. It provides an overview of
PID (proportional, integral, derivative) based servo loops, and
introduces two standard manual tuning methods that work well
for a large variety of systems. It will also provide an introduction
to the increasingly popular technique of auto-tuning, which, despite
the name, isn’t necessarily as automatic is it may seem. Finally,
we will look at advanced servo techniques such as feedforward
and frequency domain bi-quad filtering.

Using your in-tune-ition
One of the reasons PID compensators are so popular is that it
is easy to conceive of how each term contributes to the overall
output. The D (derivative) term introduces resistance or drag,
the P (proportional) term introduces a linear restoring force,
and the I (integral) introduces a time-dependent windup term.


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Tuning a Servo System
Any closed-loop servo system, whether analog or
digital, will require some tuning. This is the process
of adjusting the characteristics of the servo so that
it follows the input signal as closely as possible.
Why is tuning necessary?

A servo system is error-driven, in other words, there
must be a difference between the input and the
output before the servo will begin moving to reduce
the error. The “gain” of the system determines how
hard the servo tries to reduce the error. A high-gain
system can produce large correcting torques when
the error is very small. A high gain is required if the
output is to follow the input faithfully with minimal
error.

Now a servo motor and its load both have inertia,
which the servo amplifier must accelerate and
decelerate while attempting to follow a change at
the input. The presence of the inertia will tend to
result in over-correction, with the system oscillating
or “ringing” beyond either side of its target (Fig. 3.1).
This ringing must be damped, but too much
damping will cause the response to be sluggish.
When we tune a servo, we are trying to achieve the
fastest response with little or no overshoot.


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Tuning the P.I.D. Loop
There are two primary ways to go about selecting the P.I.D. gains. Either the operator uses a trial and error or an analytical approach. Using a trial and error approach relies significantly on the operator's own prior experience with other servo systems. The one significant downside to this is that there is no physical insight into what the gains mean and there is no way to know if the gains are optimum by any definition. However, for decades this was the approach most commonly used. In fact, it is still used today for low performance systems usually found in process control.

To address the need for an analytical approach, Ziegler and Nichols [1] proposed a method based on their many years of industrial control experience. Although they originally intended their tuning method for use in process control, their technique can be applied to servo control. Their procedure basically boils down to these two steps.
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Tuesday, April 28, 2009

servo motor control-Velocity Profiling

A velocity profile is a graph of the velocity of a motor vs. time. The area inside the curve that the velocity profile creates is the distance traveled. Velocity profiling is useful for applications where specific velocities are necessary at specific times. Two typical velocity profiles are shown in the following figures.




These two figures are both examples of velocity profiles that can be implemented using the FlexMotion hardware and software. In the first example, the motor simply accelerates to a target velocity at a specified acceleration, runs at the target velocity, and then decelerates after a certain amount of time. In the second example, the motor accelerates to a certain velocity, runs at that target velocity for a period of time, accelerates to a higher velocity, then travels at that velocity for a period of time, and then decelerates to zero.

National Instruments - Fundamentals of Motion Control
http://zone.ni.com/devzone/cda/tut/p/id/3367

Creation of velocity profile using s-curves

In this paper an approach is proposed for velocity profile control of an AC motor. The dynamic control algorithms for calculation and estimation of the S-curve profile adapt in real time to variations in system behavior to improve their performance.

The S-curve velocity profile is similar to trapezoidal, and in this case, trapezium sides are replaced by S-curves, which enables smoother velocity transitions in acceleration and deceleration periods [1, 9].

The first order trapezoidal velocity profile is a typical point-to-point move. An
axis accelerates from rest to a given velocity at a constant rate. Then traverses, or slews, to a certain point where it decelerates at a constant rate until finally, the end position is reached and the axis will come to a rest. Sometimes the slew velocity and the end position can be changed on the fly. The S-curve velocity profile can be represented as a second-order polynomial in velocity. We have an extra term here – jerk (jerk is a derivative of acceleration and a measure of impact). The second order S-curve provides complete flexibility in the control of profiles for smoothing motion and eliminating jerk from mechanical systems. The degree of S-curve on a motion
profile is controlled by separate acceleration and deceleration smoothing (jerk-limit) factors.



Fig. S-curve profile with symmetrical acceleration and deceleration periods

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Thursday, April 23, 2009

Servo Motor Motion Profiles - S-Curve

All servo systems consist of some kind of movement of a load. The method in which the load is moved is known as the motion profile. A motion profile can be as simple as a movement from point A to point B on a single axis

The S-curve motion profile allows for a gradual change in acceleration. This helps to reduce or eliminate the problems caused from overshoot, and the result is a great deal less mechanical vibration seen by the system. The minimum acceleration points occur at the beginning and end of the acceleration period, while the maximum acceleration occurs between these two points. This gives a motion profile that is fast and accurate.


Wednesday, April 22, 2009

Servo Motor Motion Profiles - Trapezoidal


All servo systems consist of some kind of movement of a load. The method in which the load is moved is known as the motion profile. A motion profile can be as simple as a movement from point A to point B on a single axis


The trapezoidal motion profile slopes the velocity curve to create predictable acceleration and deceleration rates. A trapezoidal motion profile is shown in figure 3. The time to accelerate and decelerate is precise and repeatable. Ta and Td still exist, but they are now specified values instead of random values



- If ta = td = T/3 for a trapezoidal move profile, the overall power used is a minimum
- Overshoot error still exists for a trapezoidal move, but this error is negligible for many systems.
- Higher precision machines require a different motion profile.


advancedmotioncontrols
http://www.advancedmotioncontrols.com/

Tuesday, April 21, 2009

DC Servo motor Controller with Microcontroller Project


This is an experiment on the closed loop DC servomotor control system (SMC). It will able to be used for practical use with/without some modifications. The closed loop servo mechanism requires real-time servo operations, such as position control, velocity control and torque control. It will be suitable for implementation to any embedded 32 bit RISC processors as a middleware. In this project, these operations are processed with only a cheap 8 bit microcontroller.

Hardware


Figure 1 shows the block diagram for SMC. This is built with only an AVR microcontroller and a PWM mode power amplifire. Whole of servo operation is processed by software implemented servo processor. Any analog component for servo operation is not used.Software



Figure 5 shows the servo operation for SMC. It is multiple feedback configuration which is most popular and fundamental servo mechanism at now. The servo operation which has multiple feedback, is called "Cascaded control". It is a kind of "Advanced servo mechanism". At the cascaded control, one or more control term whoes response is faster than major loop is chosen, and put it into the major control loop as minor control loop, the overall servo performance is increased.
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DSPIC Servo motor Controller Project

This project was developed as an inexpensive way to drive small dc brushed motors as positioning servos for use on a desktop sized CNC machine. The board is interfaced to the PC through 2 pins of a parallel port. The drive signal on these pins is known as quadrature drive. The power stage consists of a power op amp driven in constant current mode. The internal PIC processor ( a 30f4012 from Microchip ) is programmed in C through the C30 compiler and the Microchip IDE. The servo loop parameters are programmed through a serial port connection and are saved in the dspic eeprom. Once set for a particular drive, they should not need to be changed.
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Servo Control of a DC-Brush Motor
The PIC17C42 microcontroller is an excellent choice for
cost-effective servo control in embedded applications.
Due to its Harvard architecture and RISC features, the
PIC17C42 offers excellent computation speed needed
for real-time closed loop servo control. This application
note examines the use of the PIC17C42 as a DC brush
motor servo controller. It is shown that a PID (Proportional,
Integral, Differential) control calculation can be
performed in less than 200 us (@16 MHz) allowing control
loop sample times in the 2 kHz range. Encoder rates
up to 3 MHz are easily handled by the PIC17C42's high
speed peripherals. Further, the on-chip peripherals allow
an absolute minimum cost system to be constructed.

The servo system discussed in this application note
uses a PIC17C42 microcontroller, a programmable
logic device (PLD), and a single-chip H-bridge driver.
Such a system might be used as a positioning controller
in a printer, plotter, or scanner. The low cost of implementing
a servo control system using the PIC17C42
allows this system to compete favorably with stepper
motor systems by offering a number of advantages:
• Increased Acceleration, Velocity
• Improved Efficiency
• Reduced Audible Noise
• True Disturbance Rejection


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PICmicro DC Motor Control Tips ‘n Tricks
INTRODUCTION
Every motor control circuit can be divided into the
drive electronics and the controlling software.
These two pieces can be fairly simple or extremely
complicated depending upon the motor type, the
system requirements and the hardware/software
complexity trade-off. Generally, higher
performance systems require more complicated
hardware. This booklet describes many basic
circuits and software building blocks commonly
used to control motors. The booklet also provides
references to Microchip application notes that
describe many motor control concepts in more
detail.

Content
TIP #1: Brushed DC Motor Drive Circuits ................2
TIP #2: Brushless DC Motor Drive Circuits..............5
TIP #3: Stepper Motor Drive Circuits .......................9
TIP #4: Drive Software...........................................13
TIP #5: Writing a PWM Value to the CCP Registers
with a Mid-range PICmicro® MCU.............17
TIP #6: Current Sensing ........................................19
TIP #7: Position/Speed Sensing ............................23
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Friday, April 10, 2009

Sensorless Direct Torque Control


A Robust Sensorless Direct Torque Control of Induction
Motor Based on MRAS and Extended Kalman Filter
Abstract
In this paper, the classical Direct Torque Control (DTC) of
Induction Motor (IM) using an open loop pure integration suffers
from the well-known problems of integration especially in the
low speed operation range is detailed. To tackle this problem,
the IM variables and parameters estimation is performed using
a recursive non-linear observer known as EKF. This observer is
used to estimate the stator currents, the rotor flux linkages, the
rotor speed and the stator resistance. The main drawback of
the EKF in this case is that the load dynamics has to be known
which is not usually possible. Therefore, a new method based
on the Model Reference Adaptive System (MRAS) is used to
estimate the rotor speed. The two different nonlinear observers
applied to sensorless DTC of IM, are discussed and compared
to each other. The rotor speed estimation in DTC technique is
affected by parameter variations especially the stator
resistance due to temperature particularly at low speeds.
Therefore, it is necessary to compensate this parameter
variation in sensorless induction motor drives using an online
adaptation of the control algorithm by the estimated stator
resistance. A simulation work leads to the selected results
to support the study findings.



Direct Torque Control bloc diagram of a sensorless IM drives.
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Sensorless Direct Torque Control of an Induction Motor
Using Fuzzy Controller

Abstract:
In this paper direct torque control DTC of an induction motor is
developed. A new technique for DTC based on fuzzy logic
concept is proposed, where fast torque response with low ripple
in the stator flux and torque of induction motor can be achieved. In
comparison with the conventional DTC simulation results clearly
demonstrate a better dynamic and steady state performance with
the fuzzy logic DTC. The two approaches are explained in clear
details , which are designed using SIMULINK under Matlab Ver.6
software package. Also, MATLAB/FUZZY toolbox is used to
implement the fuzzy logic controller. Both systems are simulated
under the same conditions.
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SENSORLESS SPEED ESTIMATION OF INDUCTION MOTOR

IN A DIRECT TORQUE CONTROL SYSTEM
ABSTRACT
Fast and robust torque control in a very wide range of speed is
very needed by various industrial AC drive applications.
Therefore, since 1986 [1], direct torque control (DTC) has been
introduced to satisfy this desire. In order to achieve more
economical control, conventional speed sensor has been
replacing by sensorless speed estimation. The sensorless
schemes are used to improve reliability and decrease
maintenance requirements. In this paper, concerned sensorless
techniques of induction machine controlled by DTC algorithm
are openloop estimators and MRAS schemes [2], [3]. To
demonstrate clearly the advantages and disadvantages between
two kinds of sensorless techniques, obtained simulation results
are compared. By enhancing speed estimation, the pure
integrator is replaced by a low-pass filter to avoid DC drift and
saturation problems [2].



MRAS-based speed estimator scheme
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Sensorless three-phase induction motor direct torque
control using sliding mode control strategy

laboratory set-up for motor speed control teaching
Abstract - A three-phase induction motor direct torque
control laboratory set-up for simulation and
experimental activities is presented in this paper. It
includes both PI controllers and sliding-mode controllers
and uses a sensorless method to estimate rotor speed. The
subject of this set-up is to present to the students a
simulation tool based on Matlab SimPowerSystems
toolbox with the possibility to check simulation results
against a DSP based experimental system. The set-up
provides to the electrical engineering students an
excellent learning tool for non-linear control studies
using as example the variable speed three-phase
induction motor control.

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Thursday, April 9, 2009

Direct Torque Control of Induction Motor with FUZZY

Genetic Algorithm Optimized PI and Fuzzy Sliding Mode
Speed Control for DTC Drives
Abstract— This paper presents a detailed comparison between
a conventional PI controller and a variable structure controller
based on a fuzzy sliding mode strategy used for speed control
in direct torque control induction motor drive. Genetic algorithms
are used to tune the PI controller gains to ensure optimal
performance. The performance of the two controllers are
investigated and compared for different dynamic operating
conditions such as of reference speed and for load torque step
changes at nominal parameters and in the presence of parameter
variation and imprecision. Results show that the PI controller has
better performance for nominal operating conditions while the
fuzzy sliding mode is more robust against parameter variation
and uncertainty, and is less sensitive to external load torque
disturbances with a fast dynamic response.


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DIRECT TORQUE CONTROL OF INDUCTION MOTOR
WITH FUZZY MINIMIZATION TORQUE RIPPLE

Direct torque control (DTC) is receiving wide atten-
tion in the recent literature [1, 2]. DTC minimizes the use
of machine parameters [3, 4]. This type of control is es-
sentially a sliding mode stator flux-oriented control. The
DTC uses the hysteresis band to directly control the flux
and torque of the machine. When the stator flux falls out-
side the hysteresis band, the inverter switching stator is
changed so that the flux takes an optimal path toward
the desired value [3, 4].
The name direct torque control is derived from the
fact that on the basis of the errors between the reference
and the estimated values of torque and flux it is possible
to directly control the inverter states in order to reduce
the torque and flux errors within the prefixed band limits
[5, 6].
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IMPROVED DTC OF INDUCTION MOTOR WITH FUZZY
RESISTANCE ESTIMATOR
Abstract- The aim of the work is to study the
feasibility of stator resistance estimator in DTC
scheme. Fuzzy logic is used to estimate the stator
resistance. DTC with fuzzy estimator is characterized
by fast torque and flux response in very-low speed
operation.
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DIRECT TORQUE NEURO FUZZY SPEED CONTROL
OF AN INDUCTION MACHINE DRIVE BASED
ON A NEW VARIABLE GAIN PI CONTROLLER
This paper presents an original variable gain PI (VGPI)
controller for speed control of a simplified direct torque neuro
fuzzy controlled (DTNFC) induction motor drive. First, a
simplified direct torque neuro fuzzy control (DTNFC) for a voltage
source PWM inverter fed induction motor drive is presented.
This control scheme uses the stator flux amplitude and the
electromagnetic torque errors through a four rules adaptive NF
inference system (ANFIS) to generate a voltage space vector
(reference voltage). This voltage is used by a space vector
modulator to generate the inverter switching states. Then a VGPI
controller is designed in order to be used as the speed controller
in the simplified DTNFC induction motor drive. Simulation
of the simplified DTNFC induction motor drive using VGPI for
speed control shows promising results. The motor reaches
the reference speed rapidly and without overshoot, load
disturbances are rapidly rejected and the detuning problem
caused by the stator resistance variation is fairly well dealt with.

Direct Torque Controlled Motor Drive

Direct Torque Controlled Induction Motor Drive

Direct Torque Controlled Induction Motor Drive 1

Direct Torque Controlled Induction Motor Drive 2

Direct Torque Control of Induction Motor with FUZZY


Direct Torque Control of the Asynchronous Motor

Direct Torque Control of the Asynchronous Motor

Other

Sensorless Direct Torque Control


Wednesday, April 8, 2009

Direct Torque Control of the Asynchronous Motor


SIMULATION OF DIRECT TORQUE CONTROLLED

PERMANENT MAGNET SYNCHRONOUS MOTOR DRIVE
ABSTRACT
In this study, the structure and the control methods of
permanent magnet synchronous motor (PMSM) are
analysed and a simulation is realized using
conventional Direct Torque Control (DTC) method.
As a result of this analysis, it is observed that the
increase of the electromagnetic torque is directly
proportional to the increase of the angle between the
stator and rotor magnetic flux linkages.


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Direct Torque Control of the Asynchronous Motor
Abstract –This contribution deals with the proposal of
direct torque control (DTC) of asynchronous motor (AM)
with the help of fuzzy logic. The whole structure of DTC
is designed in software Matlab – Simulink, the fuzzy
regulator is designed with the help of Fuzzy Toolbox. The
results of DTC with fuzzy regulator are compared with
DTC with the help of Depenbrock method and DTC with
the help of Takahashi method.


Structure DTC

Tuesday, April 7, 2009

Direct Torque Controlled Induction Motor Drive 2

DIRECT TORQUE CONTROL FOR INDUCTION MOTOR
USING INTELLIGENT TECHNIQUES
ABSTRACT
In this paper, we propose two approach intelligent techniques
of improvement of Direct Torque Control (DTC) of Induction
motor such as fuzzy logic (FL) and artificial neural network (ANN),
applied in switching select voltage vector .The comparison with
conventional direct torque control (DTC), show that the use of
the DTC_FL and DTC_ANN, reduced the torque, stator flux,
and current ripples. The validity of the proposed methods is
confirmed by the simulative results.


Basic direct torque control scheme based ANN
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New Direct Torque Control Scheme of Induction Motor
for Electric Vehicles
Abstract
In this paper, new scheme of direct torque
control of induction motor for electric vehicles is
proposed and the results of an investigation into
suitable torque control schemes are also presented.
The electric vehicle drive consists of rewound
induction motors and a three-level IGBT inverter.
The schemes investigated are Field Oriented Control,
Direct Torque Control (DTC), and DTC using Space
Vector Modulation. The results of Matlab-Simulink
simulations and a comparison between the control
schemes are presented. It is found that the DTC using
Space Vector Modulation scheme is best for this
application.



Circuit Diagram of Space Vector Modulation
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EXPERIMENTAL APPROACH OF DIRECT TORQUE
CONTROL METHOD USING MATRIX CONVERTER
FED INDUCTION MOTOR
ABSTRACT
This paper presents a study on direct torque control method
(DTC) using matrix converter fed induction motor. The
advantages of matrix converters are combined with the advantages
of the DTC technique: under the constraint of unity input power
factor, the required voltage vectors are generated to implement
the conventional DTC method of induction motor. However, since
the first idea about DTC method using MC fed induction motor was
suggested by [1], the current researches just focus on some
simulation results and a little un-explicit experimental result is carried
out. This paper describes the operation of induction motor under the
DTC method in steady-state and transient conditions by the
experimental results, the discussion about the trend of DTC method
using MC is also carried out. Furthermore, the entire system of
matrix converter configuration using 7.5kW IGBT modules
(FR35R12KE3V1) is explained in detail.
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DIRECT TORQUE CONTROL STRATEGY OF
INDUCTION MOTORS

Direct Torque Control of inverter-fed Induction Machine allows
high dynamic performance by means of very simple
control schemes. In this paper various direct torque control
methodologies as conventional DTC (C_DTC), modified DTC
(M_DTC) and twelve sectors (12_DTC) have been analysed
and compared in order to evaluate the influence of the motor
operating condition on steady state performances. A particula
r emphasis on stator flux trajectory, torque ripple and stator
current distortion has been made. Simulation results show the
effectiveness of the proposed methods.
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Direct Torque Control of Induction Motors
D.C. motors have been used widely during the last
century in applications where variable-speed
operation was needed, because its flux and torque can
be controlled easily by means of changing the field
and the armature currents respectively. Furthermore,
operation in the four quadrants of the torque-speed
plane including temporary standstill was achieved.
However, DC motors have basically two drawbacks,
which are the existence of commutators and brushes.
These two disadvantages implied not only periodic
maintenance but also difficulty to work in dirty and
explosive environments; difficulty that sometimes
used to become in impossibility.
On the other hand, induction motors

Monday, April 6, 2009

Direct Torque Controlled Induction Motor Drive 1

HIGH – PERFORMANCE ADAPTIVE INTELLIGENT DIRECT
TORQUE CONTROL SCHEMES FOR INDUCTION MOTOR DRIVES


ABSTRACT This study presents a detailed comparison between
viable adaptive intelligent torque control strategies of induction
motor, emphasizing advantages and disadvantages. The scope
of this study is to choose an adaptive intelligent controller for
induction motor drive proposed for high performance applications.
Induction motors are characterized by complex, highly non-linear
and time varying dynamics and inaccessibility of some states and
output for measurements and hence can be considered as a
challenging engineering problem. The advent of torque and flux
control techniques have partially solved induction motor control
problems, because they are sensitive to drive parameter
variations and performance may deteriorate if conventional
controllers are used. Intelligent controllers are considered as
potential candidates for such an application. In this paper, the
performance of the various sensorless intelligent Direct Torque
Control (DTC) techniques of Induction motor such as neural
network, fuzzy and genetic algorithm based torque controllers
are evaluated. Adaptive intelligent techniques are applied to
achieve high performance decoupled flux and torque control.
The theoretical principle, numerical simulation procedures and
the results of these methods are discussed.



Figure 1 Basic configuration of DTC scheme



Figure 3 Schematic of DTC using Neural-Network controller



Figure 9 Schematic of fuzzy logic DTC
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DIRECT TORQUE CONTROLLED INDUCTION MOTOR DRIVE
UTILIZED IN AN ELECTRICAL VEHICLE
A new developed Direct Torque Control principle is used for torque
and stator flux control. Very fast torque response -- typically less
than 2ms -~ can be obtained. A very accurate stator flux observer is
an essential part of the complete concept. Due to this observer no
speed sensor is needed.
more pdf


Improved direct torque control of induction motor with
dither injection

Abstract. In this paper, a three-level inverter-fed induction motor
drive operating under Direct Torque Control (DTC) is presented
.Atriangularwave is used as dither signal of minute amplitude
(for torque hysteresis band and flux hysteresis band respectively)
in the error block. This method minimizes flux and torque ripple in a
three-level inverter fed induction motor drive while the dynamic
performance is not affected. The optimal value of dither frequency
and magnitude is found out under free running condition. The
proposed technique reduces torque ripple by 60% (peak to peak)
compared to the case without dither injection, results in low acoustic
noise and increases the switching frequency of the inverter. A
laboratory prototype of the drive system has been developed and
the simulation and experimental results are reported.


Block diagram of three-level inverter-fed DTC induction motor drive.
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Direct Torque Control of Induction Motor Using
Sophisticated Lookup Tables Based on Neural Networks

Abstract
Induction motor drive based on direct torque control
(DTC) allows high dynamic performance to be obtained
with very simple hysteresis control scheme. Direct
control of the torque and flux is achieved by proper
selection of inverter voltage space vector through a
lookup table .In this paper apart from six sector look up
table used for classical DTC, a modified look up table,
which also use six sectors but with different zones and a
twelve sector table are presented .This paper also
presents the application of neural networks to control
induction machines with DTC. Neural network is used to
emulate the state selector of the DTC. In this paper
Levenberg-Marquardt algorithm is used to train the
neural network. Finally DTC is simulated with and
without neural networks and results are compared.
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DIRECT TORQUE CONTROLLED PWM
INVERTER FED INDUCTION MOTOR DRIVE FOR
CITY TRANSPORTATION
In this paper an application of Direct Torque Control with Space
Vector Modulation (DTC– SVM) controlled induction motor for
tram drive is presented. Thanks to its advantages like: excellent
dynamics, low torque ripples, insensitivity for motor parameters
changes, constant switching and low sampling frequency,
DTC–SVM is used in various applications. In proposed case
DTC–SVM is used for tram traction drive based on PWM Voltage
Sourced Inverter Fed Induction Machine. This method was chosen
after comparison with Field Oriented Control (FOC), Switching
Table Direct Torque Control (ST–DTC) and Direct Self Control
(DSC). DTC–SVM combines advantages and eliminates
drawbacks commonly used methods like FOC and ST–DTC.
There are no hysteresis controllers, what gives possibility to
reduce sampling and also switching frequency. It leads to reduce
switching loses (important in high power applications).

Constant switching frequency is ensured by using Space Vector
Modulation strategy. In DTC–SVM linear PI regulators are used.
Both stator flux and electromagnetic torque are controlled directly.
High dynamics is achieved and also good stationary operation
performance is kept. This advantages allow to implement
DTC–SVM for traction drives. The paper presents parallel structure
of DTC–SVM. Operating ranges, including field weakening
region, are described. Some experimental results of the 75kW
induction motor drive which illustrate its performance are attached.

Sunday, April 5, 2009

Types of Induction Motor Drive Controllers

There are many different ways to drive an induction
motor. The main differences between them are the
motor’s performance and the viability and cost in its
real implementation.

1.1- Voltage/Frequency:
Despite the fact that V/F is the simplest controller, it
is the most widespread, reaching approximately 90%
of the industrial applications. It is known as a scalar
control and acts imposing a constant relation between
voltage and frequency. The structure is very simple
and it is normally used without speed feedback.
However, this controller doesn’t achieve a good
accuracy in both speed and torque responses mainly
due to the fact that the stator flux and the torque are
not directly controlled. Even though, as long as the
parameters are identified, the accuracy in the speed
can be 2% (except in a very low speed) and the
dynamic response can be approximately around 50ms
.

1.2- Vector Controllers:
In these types of controllers, there are control loops
for controlling both the torque and the flux . The
most spread controllers are the ones that use vector
transform such as either Park or Ku. Its accuracy can
reach values such as 0.5% regarding the speed and
2% regarding the torque, even in stand still.
The main disadvantages are the huge computational
capability required and the compulsory good
identification of the motor parameters.

1.3- Field Acceleration Method:
This method is based on maintaining the amplitude
and the phase of the stator current constants, avoiding
electromagnetic transients. Therefore the equations
used can be simplified saving the vector
transformation in the controllers.
It is achieved some computational reduction,
overcoming the main problem in the vector
controllers and then becoming an important
alternative for the vector controllers.

source
http://www.jcee.upc.es/JCEE2001/PDFs%202000/
8arias.pdf

Thursday, April 2, 2009

Servo motor control - Feedforward with PIV control

Fundamentals of servo motion control

Feedforward control
That missing ingredient provided we have access to both
Velocity and acceleration commands, synched up with
position commands is feedforward control.

An example of how feedforward control may be used in
parallel with disturbance rejection control is shown
in figure 8. The key is to accurately calculate the amount
of torque required to make each move a priori. To do so,
we take the basic equation of motion




and approximate it (as follows) because the disturbance
torque Td is unknown.



more pdf



Fundamentals of Servo Motion Control
Feedforward Control
In order to achieve near zero following or tracking error,
feedforward control is often employed. A requirement for
feedforward control is the availability of both the velocity,
and acceleration, commands synchronized with the
position commands,. An example of how feedforward
control is used in addition to disturbance rejection control is
shown in Fig. 8.





Figure 8. Basic Feedforward and P.I .V. Control Topology.

Wednesday, April 1, 2009

AC Servo Motor Control Algorithm

A precise control of AC servo motor using neural
network PID controller
A new control technique based on a neural network, is proposed
here for control of AC servo motors. The PID control is widely
used in servo systems as it has simple structure, safety and
reliability. However, it has certain problems in a complex system,
resulting in imperfect action in the presence of uncertain
parameters. To solve these problems, a new hybrid control
algorithm of the PID controller is proposed, which could
prove the adequacy of the proposed control algorithm through
simulation and experiments after driving the AC
servo motor system using neural network PID controller.

Structure of PID controller using neural network control




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Position Control of an AC Servo Motor Using
VHDL & FPGA


Abstract
In this paper, a new method of controlling position of
AC Servomotor using Field Programmable Gate Array (FPGA).
FPGA controller is used to generate direction and the number of
pulses required to rotate for a given angle. Pulses are sent as a square
wave, the number of pulses determines the angle of rotation and
frequency of square wave determines the speed of rotation. The
proposed control scheme has been realized using XILINX FPGA
SPARTAN XC3S400 and tested using MUMA012PIS model
Alternating Current (AC) servomotor. Experimental results show that
the position of the AC Servo motor can be controlled effectively.

INTRODUCTION
A servo motor is an Electro-mechanical device in which the
electrical input determines the position of the armature of
a motor. The shaft of the servo motor can be positioned to a
specific angle by sending the coded signal. The AC servo
motors have been widely used in the industrial fields and
various approaches have been made to realize high
performance motion control. These can be effectively utilized
in many position control systems subjected to external
disturbances such as friction.
With successively improving reliability and performance of
digital controllers, the digital control techniques have
predominated over other analog counter parts. The advantages
of digital controllers are:



• Reconfigurability
• Power saving options
• Less external passive components
• Less sensitive to temperature variation
• High efficiency







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New Digital Hardware Control Method for High
Performance AC Servo Motor


Abstract:
Today’s motor drives widely use Digital Signal
Processor (DSP) or Microcontroller to
implement the digital control algorithm. Most
recently new requirements have arisen. These
include faster torque control update with flexible
design capability of motion peripherals for high
performance military servo drive applications.
A Complete digital hardware based AC servo
drive development system has been developed to
satisfy increasing demand for performance
enhancement. Based on the FPGA, the system is
configurable for either induction or permanent
magnet machine servo control. The detail design
of complete hardware based high performance
AC servo drive system is discussed.





Control Block Diagram

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FPGA Based Speed Control of AC Servomotor
Using Sinusoidal PWM


Abstract
This paper presents a Xilinx Field Programmable Gate Array
(FPGA) based speed control of AC Servomotor using sinusoidal
PWM technique. Xilinx FPGA is a programmable logic device
developed by Xilinx which is considered as an efficient hardware
for rapid prototyping. It is used to generate 50 Hz sine wave, the
triangular wave and the sinusoidal PWM signals. The sinusoidal
pulse width controls the speed of Motor. The proposed control
scheme has been realized using Xilinx FPGA SPARTAN
XC3S400 and tested using SM115 model Alternating Current
(AC) servomotor. The result provides a controllable speed with
satisfactory dynamic and static performances.