This document describes a rapid battery charger that uses a fuzzy logic controller. It discusses nickel-cadmium batteries, the need for a fast charger, and how fuzzy logic differs from classical logic. It then explains the components of a fuzzy controller including membership functions. The document outlines the modeling, simulation steps, and basics of fuzzy logic control. Graphs of membership functions and block diagrams of the simulation in MATLAB are included. The conclusion states that the fuzzy controller provides a safe, stable, and optimized charging process. Future work could optimize additional parameters of the fuzzy system to improve performance further.
Automatic car parking mechanism using neuro fuzzy controller tuned by genetic...SumitDutta58
This paper has being presented a neuro fuzzy controller
based on Gaussian type RBF neural network, where all the
parameters can be simultaneously tuned by GA. By
appropriate coding of NFLC parameters it can achieve self
tuning properties from an initial random state.
Automatic car parking mechanism using neuro fuzzy controller tuned by genetic...SumitDutta58
This paper has being presented a neuro fuzzy controller
based on Gaussian type RBF neural network, where all the
parameters can be simultaneously tuned by GA. By
appropriate coding of NFLC parameters it can achieve self
tuning properties from an initial random state.
Design and Implementation of Single Precision Pipelined Floating Point Co-Pro...Silicon Mentor
Floating point numbers are used in various applications such as medical imaging, radar, telecommunications Etc. This paper deals with the comparison of various arithmetic modules and the implementation of optimized floating point ALU. For more info download this file or visit us at:
http://www.siliconmentor.com/
Modeling & Simulation of CubeSat-based Missions'Concept of OperationsObeo
Discover how Arcadia/Capella is used to model and simulate concept of operations scenarios for CubeSat-based missions. During this webinar, Danilo Pallamin de Almeida, who worked as a Space Systems Engineer for the NanosatC-BR2 mission at INPE, the Brazilian Institute for Space Research, will present how CubeSat-based missions have been modeled with Capella.
The model describing an initial architecture mission and concept of operations (CONOPS) is used to generate a script that configures a satellite simulator with the corresponding mission parameters.
You will see how it allows the INPE to:
- run concept of operations scenarios simulations,
- use the results for power/data-budget analyses and trade studies
Innovative Solar Array Drive Assembly for CubeSat SatelliteMichele Marino
The CubeSat satellite is a smart option for reliable and low cost space mission development. Growing
CubeSat performances lead to more extensive nanosatellite application. Currently,
Telecommunication and Earth Observation missions are under development both in single and
constellation configurations. The main targets for the future nanosatellite are: accurate attitude
pointing, high data rate transfer, increased power generation. The on board power/energy availability
reduces or limits the CubeSat performances in terms of processing capabilities, power transmission
and attitude/orbit maneuvers. Following these constraints, the IMT has developed an innovative unit,
named nano-Solar Array Drive Assembly (SADA) for 3U CubeSat, with the aim of increasing the
photovoltaic energy generation (up to an average 35W EOL). It is composed by two independent
Solar Arrays (Wings Assembly) and Rotatory Mechanisms / Logical Unit (SAC – Solar Array
Control). The aim of SADA is to align constantly the two Solar Arrays to the Sun direction, around
one axis. The rotatory system is composed by drive gear sets, stepper motors and slip rings. The high
value of gearhead reduction ratio and two dedicated photodiodes (as solar sensors) allow a fine
pointing accuracy (<5°). Several operation modes are implemented and controlled by the On Board
Computer through the I2C and CAN buses: autonomous (sun detection and pointing), slave or
cooperative. An advanced and smart control algorithm was developed and implemented in the logic
unit. The Solar Array points along the maximum solar flux direction, maximum output speed up to
4°/s (step size 0.004°). A system failure control avoids the thermal and power damaging in case one
or both wings are blocked. SADA is fully compliant with all CubeSat form factor (3U or greater) and
BUS (CSKB – CubeSat Kit Bus). The Solar Wings, during the launch phase, are stowed beside the
CubeSat structure (opposite side faces). The overall thickness is less than 9 mm, compliant to ISIPOD
dispenser. The Logical and Drive unit (SAC), small (90 x 90 x 12 mm) and light (185 gr), is allocated inside the satellite. The Wings are electrically connected to the SAC, by means of two 16 channels
slip rings (1A per contact) for a continuous rotation, without cable saturation. The Alignment
Calibration System assures that the unit runs correctly up to 10 mm of misalignment between the
SAC and the geometric satellite center, along Z direction. The generated power is not handled by
SAC, but by PDU through Standard Molex Connectors. The two wings, stowed during the launch
phase, are deployed in orbit. In order to increase the system reliability, the deployment is based on
two redundant thermal cutter systems. In the final configuration, the 3U CubeSat has two wings, each
one 300 x 300 mm and 36 AzurSpace 3J solar cells.
[Capella Day 2019] Model execution and system simulation in CapellaObeo
A common need in system architecture design is to verify that if the architect is correct and can satisfy its requirements. Execution of system architect model means to interact with state machines to test system’s control logic. It can verify if the logical sequences of functions and interfaces in different scenarios are desired.
However, only sequence itself is not enough to verify its consequence or output. So we need each function to do what it is supposed to do during model execution to verify its output, and that is what we called “system simulation”.
This presentation introduces how we do model execution in Capella, and how to embed digital mockup inside functions to do “system simulation” with a higher confidence.
Renfei Xu, Glaway
Renfei Xu is the technical manager of MBSE solution in Glaway. He has participated in many pilot projects of MBSE in areas like Engine Control, Avionics, Mechatronics and so on. In recent years, he is responsible for the deployment of MBSE using Capella and ARCADIA methodology in a Radar research institute.
Wenhua Fang, Glaway
Wenhua Fang is the Director of Systems Engineering in Glaway. He has more than 12 years of working experience in SE.
He is responsible for more than 10 implementation projects of MBSE in areas like Aircraft, Engine Control, Avionics, Automotive and so on. In recent years, he leads the team to deploy MBSE in China(including using Capella and ARCADIA methodology).
Modern Tools for the Small-Signal Stability Analysis and Design of FACTS Assi...Power System Operation
There has recently been an intense development of eigenanalysis tools for power systems dynamics and control. This paper provides an up-to-date review of the major algorithms available. Comments on other relevant but yet unpublished algorithms are also made.
The conventional state-space description is obtained through the elimination of the algebraic variables of the mathematical model. In many applications, the power system case included, the algebraic variables in the model are usually more numerous than the state variables.
The problem of multiple, decentralized controller synthesis in large, FACTS assisted power systems is addressed.
A report in CIGRE [1] recognized the large benefits of working with the unreduced set of differential-algebraic equations linearized at an operating point. The resulting power system Jacobian is large and highly sparse, allowing efficient use of sparsity oriented programming. The computation of all system eigenvalues, not practical for large power systems, was since then replaced by the computation of only the eigenvalues of interest.
A good part of the paper is dedicated to showing the high productivity gains achieved when using a well designed package for graphical display and animation of results.
The pressing needs for better utilization of existing transmission and generation equipment will eventually dictate a wider use of FACTS devices. The higher complexity and stricter requirements on power system controls, under both steady-state and dynamic conditions, calls for the immediate development and use of more sophisticated computer tools. The material in this paper may help the further development of one of these tools.
Many important developments occurred in the last fifteen
A comparative study of full adder using static cmos logic styleeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
for more details contact:
SR INFO SYSTEMS
Firestation Square, Baramunda, Bhubaneswar
You can visit our website :
www.bputproject.com
www.liveprojects.co.in
www.srinfosystems.com
Design and Implementation of Single Precision Pipelined Floating Point Co-Pro...Silicon Mentor
Floating point numbers are used in various applications such as medical imaging, radar, telecommunications Etc. This paper deals with the comparison of various arithmetic modules and the implementation of optimized floating point ALU. For more info download this file or visit us at:
http://www.siliconmentor.com/
Modeling & Simulation of CubeSat-based Missions'Concept of OperationsObeo
Discover how Arcadia/Capella is used to model and simulate concept of operations scenarios for CubeSat-based missions. During this webinar, Danilo Pallamin de Almeida, who worked as a Space Systems Engineer for the NanosatC-BR2 mission at INPE, the Brazilian Institute for Space Research, will present how CubeSat-based missions have been modeled with Capella.
The model describing an initial architecture mission and concept of operations (CONOPS) is used to generate a script that configures a satellite simulator with the corresponding mission parameters.
You will see how it allows the INPE to:
- run concept of operations scenarios simulations,
- use the results for power/data-budget analyses and trade studies
Innovative Solar Array Drive Assembly for CubeSat SatelliteMichele Marino
The CubeSat satellite is a smart option for reliable and low cost space mission development. Growing
CubeSat performances lead to more extensive nanosatellite application. Currently,
Telecommunication and Earth Observation missions are under development both in single and
constellation configurations. The main targets for the future nanosatellite are: accurate attitude
pointing, high data rate transfer, increased power generation. The on board power/energy availability
reduces or limits the CubeSat performances in terms of processing capabilities, power transmission
and attitude/orbit maneuvers. Following these constraints, the IMT has developed an innovative unit,
named nano-Solar Array Drive Assembly (SADA) for 3U CubeSat, with the aim of increasing the
photovoltaic energy generation (up to an average 35W EOL). It is composed by two independent
Solar Arrays (Wings Assembly) and Rotatory Mechanisms / Logical Unit (SAC – Solar Array
Control). The aim of SADA is to align constantly the two Solar Arrays to the Sun direction, around
one axis. The rotatory system is composed by drive gear sets, stepper motors and slip rings. The high
value of gearhead reduction ratio and two dedicated photodiodes (as solar sensors) allow a fine
pointing accuracy (<5°). Several operation modes are implemented and controlled by the On Board
Computer through the I2C and CAN buses: autonomous (sun detection and pointing), slave or
cooperative. An advanced and smart control algorithm was developed and implemented in the logic
unit. The Solar Array points along the maximum solar flux direction, maximum output speed up to
4°/s (step size 0.004°). A system failure control avoids the thermal and power damaging in case one
or both wings are blocked. SADA is fully compliant with all CubeSat form factor (3U or greater) and
BUS (CSKB – CubeSat Kit Bus). The Solar Wings, during the launch phase, are stowed beside the
CubeSat structure (opposite side faces). The overall thickness is less than 9 mm, compliant to ISIPOD
dispenser. The Logical and Drive unit (SAC), small (90 x 90 x 12 mm) and light (185 gr), is allocated inside the satellite. The Wings are electrically connected to the SAC, by means of two 16 channels
slip rings (1A per contact) for a continuous rotation, without cable saturation. The Alignment
Calibration System assures that the unit runs correctly up to 10 mm of misalignment between the
SAC and the geometric satellite center, along Z direction. The generated power is not handled by
SAC, but by PDU through Standard Molex Connectors. The two wings, stowed during the launch
phase, are deployed in orbit. In order to increase the system reliability, the deployment is based on
two redundant thermal cutter systems. In the final configuration, the 3U CubeSat has two wings, each
one 300 x 300 mm and 36 AzurSpace 3J solar cells.
[Capella Day 2019] Model execution and system simulation in CapellaObeo
A common need in system architecture design is to verify that if the architect is correct and can satisfy its requirements. Execution of system architect model means to interact with state machines to test system’s control logic. It can verify if the logical sequences of functions and interfaces in different scenarios are desired.
However, only sequence itself is not enough to verify its consequence or output. So we need each function to do what it is supposed to do during model execution to verify its output, and that is what we called “system simulation”.
This presentation introduces how we do model execution in Capella, and how to embed digital mockup inside functions to do “system simulation” with a higher confidence.
Renfei Xu, Glaway
Renfei Xu is the technical manager of MBSE solution in Glaway. He has participated in many pilot projects of MBSE in areas like Engine Control, Avionics, Mechatronics and so on. In recent years, he is responsible for the deployment of MBSE using Capella and ARCADIA methodology in a Radar research institute.
Wenhua Fang, Glaway
Wenhua Fang is the Director of Systems Engineering in Glaway. He has more than 12 years of working experience in SE.
He is responsible for more than 10 implementation projects of MBSE in areas like Aircraft, Engine Control, Avionics, Automotive and so on. In recent years, he leads the team to deploy MBSE in China(including using Capella and ARCADIA methodology).
Modern Tools for the Small-Signal Stability Analysis and Design of FACTS Assi...Power System Operation
There has recently been an intense development of eigenanalysis tools for power systems dynamics and control. This paper provides an up-to-date review of the major algorithms available. Comments on other relevant but yet unpublished algorithms are also made.
The conventional state-space description is obtained through the elimination of the algebraic variables of the mathematical model. In many applications, the power system case included, the algebraic variables in the model are usually more numerous than the state variables.
The problem of multiple, decentralized controller synthesis in large, FACTS assisted power systems is addressed.
A report in CIGRE [1] recognized the large benefits of working with the unreduced set of differential-algebraic equations linearized at an operating point. The resulting power system Jacobian is large and highly sparse, allowing efficient use of sparsity oriented programming. The computation of all system eigenvalues, not practical for large power systems, was since then replaced by the computation of only the eigenvalues of interest.
A good part of the paper is dedicated to showing the high productivity gains achieved when using a well designed package for graphical display and animation of results.
The pressing needs for better utilization of existing transmission and generation equipment will eventually dictate a wider use of FACTS devices. The higher complexity and stricter requirements on power system controls, under both steady-state and dynamic conditions, calls for the immediate development and use of more sophisticated computer tools. The material in this paper may help the further development of one of these tools.
Many important developments occurred in the last fifteen
A comparative study of full adder using static cmos logic styleeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
for more details contact:
SR INFO SYSTEMS
Firestation Square, Baramunda, Bhubaneswar
You can visit our website :
www.bputproject.com
www.liveprojects.co.in
www.srinfosystems.com
This work shows the design and tuning procedure of a discrete PID controller for regulating buck boost converter circuits. The buck boost converter model is implemented using Simscape Matlab library without having to derive a complex mathematical model. A new tuning process of digital PID controllers based on identification data has been proposed. Simulation results are introduced to examine the potentials of the designed controller in power electronic applications and validate the capability and stability of the controller under supply and load perturbations. Despite controller linearity, the new approach has proved to be successful even with highly nonlinear systems. The proposed controller has succeeded in rejecting all the disturbances effectively and maintaining a constant output voltage from the regulator.
Design of Fuzzy Logic Controller for Speed Regulation of BLDC motor using MATLABijsrd.com
Brushless DC (BLDC) motors drives are one of the electrical drives that are rapidly gaining popularity, due to their high efficiency, good dynamic response and low maintenance. The design and development of a BLDC motor drive for commercial applications is presented. The aim of paper is to design a simulation model of inverter fed PMBLDC motor with Fuzzy logic controller. Fuzzy logic controller is developed using fuzzy logic tool box which is available in Matlab. FIS editor used to create .FIS file which contains the Fuzzy Logic Membership function and Rule base. And membership functions of desired output. After creating .FIS file it is implemented in the Matlab Simulink. And the BLDC motor is run satisfactorily using the Fuzzy logic controller.
Training report prepared on PLC on CNC at BHEL,Hyderabad. It have sufficient slides to know the basics about PLC on CNC and working of that with coding. It was worth learning on BHEL.
https://technoelectronics44.blogspot.com/
GDI TECHNOLOGY, here you get GDI implementation and design of GDI based gates AND, OR, XOR, and Adders like CLA, CIA, CSKA, performance analysis of CMOS And GDI
A Standard-Cell Solution to a Ten-Cell Problem: The Development of a State-of...jgpecor
Numerous solutions exist for determining and displaying battery state-of-charge information. The sharp increase in popularity of portable personal electronics in the commercial world, coupled with the migration toward highly mobile dismounted-soldier communications and weapons technology, has lead to a multitude of battery management integrated circuits (ICs) from leading vendors in the semiconductor industry. Unfortunately, very few of the ICs are targeted for implementation in primary batteries – especially batteries with the unique attributes that often characterize primary lithium batteries. As a result, finding an existing semiconductor solution for state-of-charge determination in primary lithium batteries is a challenging endeavor.
This paper presents the development process of an application-specific integrated circuit (ASIC) targeted for implementation into primary lithium batteries. Specifically, this ASIC was developed to address the need for a state-of-charge solution in the BA-5590 LiSO2 and BA-5390 LiMnO2.
3. BRIEF
Rapid Battery
Charger Using
Fuzzy Controller is,
modern
technology which
are being utilized
these days;
based on Fuzzy
Logic,
which is quite
different from
classical Boolean
logic.
Fuzzy logic is
widely used in
machine control.
4. NI-CD BATTERY
• using nickel oxide hydroxide and
• metallic cadmium as electrodes.
The nickel–cadmium
battery (NiCd
battery or NiCad
battery) is a type
of rechargeable
battery
• but without doing any damage to
them.
The main objective for
the development of
rapid battery charger
was to charge the Ni-
Cd batteries quickly,
5. Since the behavior of Ni-Cd
batteries at very high
charging rates was not
available,
• so there was need to
obtain them through
experimentation.
• Based on the upper limit of
the charging current as
fixed at 8C i.e. 4A, since
batteries with capacity
C=500 mAh were the target
batteries.
Based on the rigorous
experimentation with the Ni-
Cd batteries,
• it was observed that the
two input variables used to
control the charging rate
(Ct) are absolute
temperature of the
batteries (T) and its
temperature gradient
(dT/dt).
• Universe of discourse for a
variable is defined as its
working range.
6. FUZZY CONTROLLER
A fuzzy control system or
fuzzy controller is
a control system based
on fuzzy logic—
• a mathematical system that
analyzes analog input values in terms
of logical variables that take on
continuous values between 0 and 1,
• in contrast to classical or digital logic,
which operates on discrete values of
either 1 or 0.
7. HISTORY
Fuzzy logic was first
proposed by Lotfi A.
Zadeh.
He elaborated on his
ideas in a 1973
paper
that introduced the
concept of "linguistic
variables",
which equates to a
variable defined as a
fuzzy set.
8. Applications:
Research and
development is also
continuing on fuzzy
applications in software,
as opposed to firmware,
design,
• so-called adaptive "genetic" software
systems, with the ultimate goal of building
"self-learning" fuzzy-control systems.
including fuzzy expert
systems and integration
of fuzzy logic
with neural-network and
10. MATLAB (Matrix Laboratory) is
a numerical computing environment
and fourth-generation programming
language.
Developed by MathWorks, MATLAB
allows matrix manipulations,
• plotting of functions and data,
implementation of algorithms,
• creation of user interfaces, and interfacing
with programs written in other languages,
• including C, C++, Java,
• and Fortran.
11. Simulink,
• developed by MathWorks,
• is a data flow graphical programming
language tool for modeling,
• simulating and analyzing
multidomain dynamic systems.
• Its primary interface is a graphical block
diagramming tool and a customizable set of
block libraries.
Simulink is widely used in control
theory and digital signal
processing for multidomain
simulation and Model-Based
Design.
12. BASICS OF FUZZY CONTROLLER
• A Fuzzifier, which converts input
data into suitable linguistic
values;
• a fuzzy rule base, which consists
of a database with the necessary
linguistic definitions and the
control rule set;
• a fuzzy inference engine which
simulating a human decision
process, that infers the fuzzy
control action from the
knowledge of the control rules
and finally linguistic variable
definitions;
• a Defuzzifier, which yields a
nonfuzzy control action from an
inferred fuzzy control action.
13. Membership
Functions
Fuzzy sets must be defined
for each input and output
variable.
As shown in Figure , four
fuzzy Subsets (ZERO, SMALL,
MEDUM, HIGH) have been
chosen for charge current
while only two fuzzy subsets
(SMALL, HIGH),
• have been selected
for the Battery
temperature and
voltage changes in
order to smooth the
control action.
14.
15.
16.
17.
18.
19. This & Above Figures are the Membership Functions of Rapid Battery
Charger.
20. The first step in the
fuzzy controller
definition is to
select input and
output variables.
Block diagram of
the fuzzy controller
structure show that
we have two input
variable (battery
temperature and
output voltage)
While the only
output variable is
charge current as an
external signal to
switch duty-cycle.
Fuzzy controller is
simulated in fuzzy
toolbox of MATLAB
software.
21. SIMULATION
STEPS
MATLAB simulation
toolbox is strong
graphical software
for analyzing of
control systems.
The system contains
three important
blocks, fuzzy
controller,
BUCK converter and
the battery.
The basic scheme of
a general-purpose
fuzzy controlled
battery charger is
shown in Figure.
24. Derivation Of Control Rules
Fuzzy control rules are
obtained from the analysis
of the system behavior.
In their formulation it must
be considered that using
different control laws
depending on the
operating conditions can
greatly improve the battery
charger performances.
The improved
performances are the
dynamic response and
robustness.
27. Conclusion:
As a final result, it is shown
that fuzzy controller provides
a safe and stable charge
process with optimized time
and acceptable temperature
variations.
This fast and safe method is
used to charge a set of Ni-Cd
batteries and the charge time
is 100 min and temperature
during charge process doesn't
exceed from 40°C
This system can be used to
charge batteries with different
characteristics because of it's
independence to state
variables and system model
28. Future Scope
The suggested framework can
be extended to increase the
flexibility of the search
by incorporating additional
parameters so that the search
for optimal solution could be
executed in terms of number of
membership functions for each
variable,
the type of membership
function and the number of
iterations &
possibly trying variants of PSO
algorithm for identifying fuzzy
systems with an objective to
improve their performance
further.