Palestra ministrada no Agile Floripa em 18/03/2017 mostrando um novo conceito para os testes. É apresentado o testador desde os modelos iniciais de atividades (testador 1.0), passando pelo testador ágil (2.0 e 3.0) para depois apresentar o conceito da morte do testador.
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CONTROL SYSTEMS PPT ON A LEAD COMPENSATOR CHARACTERISTICS USING BODE DIAGRAM ...sanjay kumar pediredla
A LEAD COMPENSATOR CHARACTERISTICS USING BODE DIAGRAM FOR MAXIMUM OF 50 DEG PHASE ANGLE
THIS PPT IS SO USEFUL FOR THE ENGINEERING STUDENTS FOR CONTROL SYSTEMS STUDENTS AND THIS PPT ALSO CONTAINS A MATLAB CODING FOR THE LEAD COMPENSATOR AND THE RESULTS ARE ALSO PLOTTED IN THAT PPT AND THE PROBLEM CAN ALSO BE SOLVED BY USING THE DATA IN PPT AND IT IS SO USEFUL PPT
THIS DOCUMENT MAINLY CONTAINS THE HOW TO MODLE DC SERVO MOTOR BY USING THE MATLAB SIMULINK AND HOW IT WILL BEHAVE IS SHOWN IN THE MATHEMATICAL EQUATIONS AND THE PLOTTINGS ARE ALSO KEPT IN THIS DOCUMENT SO BY THIS IT IS USEFUL TO STUDY THE CHARACTRISTICS OF A DC SERVO MOTOR
Comparative Analysis of PID, SMC, SMC with PID Controller for Speed Control o...IJMTST Journal
In this thesis, sliding mode control (SMC) technique is used to control the speed of DC motor. The performance of the SMC is judged via MATLAB simulations using linear model of the DC motor and known disturbance. SMC is then compared with PID controller. The simulation result shows that the sliding mode controller (SMC) is superior controller than PID for the speed control of DC motor. Since the SMC is robust in presence of disturbances, the desired speed is perfectly tracked. The sliding mode control (SMC)can adapt itself to the parameter variations and external disturbances, problem of chattering parameter, resulting from discontinuous controller, is handled by sliding with smooth control action
This paper compares the performances of standard surrogate models in the development of an optimal control framework. The optimal control strategy is implemented on an Active Thermoelectric (ATE) window design. The ATE window design uses thermoelectric units to actively regulate the overall thermodynamic properties of the windows. The optimization of the design is a multiobjective problem, where both the heat transferred through the window and electric power consumption are minimized. The power supplies and the heat transfer are optimized under a reasonable number of randomly sampled environmental conditions. The subsequent optimal designs obtained are represented as functions of the corresponding environmental conditions using surrogate models. To this end, four types of surrogate models are used, namely, (i) Quadratic Response Surface Methodology (QRSM), (ii) Radial Basis Functions (RBF), (iii) Extended Radial Basis Functions (E-RBF), and (iv) Kriging. Their performances are compared using two accuracy measurement metrics: Root Mean Squared Error (RMSE) and Maximum Absolute Error (MAE). We found that any one of the surrogate modeling methods is not superior to the others over the whole domain for the optimal control of the ATE window.
Debabrata Pal, Aksum University, College of Engineering and Technology Department of Electrical and Computer Engineering Ethiopia, NE Africa, Email:debuoisi@gmail.com,website:www.ijrd.in
Power System Analysis was a core subject for Electrical & Electronics Engineering, Based On Anna University Syllabus. The Whole Subject was there in this document.
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Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
1. University of the South Pacific
Faculty of Science & Technology
School of Engineering & Physics
Electrical & Electronics Engineering Discipline
EE321 POWER SYSTEM ANALYSIS
LAB 2: Analyze fundamental components of power systems using object
oriented programming
Group Members: Bernadette Pesamino s11102091
Seci Durivou s11098325
Tevita Daivalu s 11090790
Eddie Arukelana s1109****
2. AIM
Analyze important power system components by making the necessary manual
calculations and comparing the results with the results simulated obtained in MATLAB
and Simscape Power Systems.
Finds how Transformer and efficiency behaves and implementing it in Matlab.
3. ALGORITHM
Question 1
Finding the primary Voltage:
Primary Current
Equivalent Circuit Referred to the
high Voltage Side
Power Factor
Leading or
Lagging
Leading
<+36.87
Lagging
<-36.87
Primary Voltage
Voltage Regulations
12. Q2
Flowchart:
Algorithm
Draw an impedance diagram for the electric power system shown in Figure
26 showing all impedances in per unit on a 100-MVA base. Choose 20 kV as the
voltage base for generator. The three-phase power and line-line ratings are
given below.
G1: 90 MVA 20 kV X = 9%
T1: 80 MVA 20/200 kV X = 16%
T2: 80 MVA 200/20 kV X = 20%
G2: 90 MVA 18 kV X = 9%
Line: 200 kV X = 120Ω
Load: 200 kV S = 48 MW +j64 Mvar
Calculate the
base voltages
each side of the
transformers
Calculate the
generator &
transformer
reactance
Calculate the
base impedance
for the
transmission line
Calculate the per
unit reactance of
the line
Calculate the
load impedance
in ohms
Calculate the
load impedance
in per unit
Draw equivalent
impedance diagram
using calculated
reactance in per unit
values
13. Base voltages
𝑉𝑏 𝑅1 = 20𝑘 (
200𝑘
20𝑘
) = 200𝑘𝑉 (Secondary side of T1)
𝑉𝑏 𝑅2 = 200𝑘𝑉 (secondary side of T1 & primary side of T2)
𝑉𝑏 𝑅3 = 200𝑘 (
200𝑘
20𝑘
) = 20𝑘𝑉 (secondary side of T2)
Reactances (per unit) of the generators & transformers using a new base
of 100MVA
𝑋 𝑛𝑒𝑤 = 𝑋 𝑜𝑙𝑑 (
𝑆 𝑛𝑒𝑤
𝑆 𝑜𝑙𝑑
) (
𝑉𝑜𝑙𝑑
𝑉𝑛 𝑒𝑤
)
2
o Generator 1:
𝑋 𝑏 𝐺1 = (0.09) (
100𝑀
90𝑀
) (
20𝑘
20𝑘
)
2
= 0.1𝑝𝑢
o Transformer 1:
𝑋 𝑏 𝑇1 = (0.16) (
100𝑀
80𝑀
) (
20𝑘
20𝑘
)
2
= 0.2𝑝𝑢
o Transformer 2:
𝑋 𝑏 𝐺2 = (0.2) (
100𝑀
90𝑀
) (
20𝑘
20𝑘
)
2
= 0.22𝑝𝑢
o Generator 2:
𝑋 𝑏 𝐺2 = (0.09) (
100𝑀
90𝑀
) (
20𝑘
20𝑘
)
2
= 0.2.1
o Base impedance of transmission lines
𝑍 𝑏 𝐿𝑖𝑛𝑒 =
𝑉𝑏
2
𝑆
=
(200𝑘)2
100
= 400Ω
o Obtaining the pu value from ohms:
15. DISCUSSION
- The efficiency of a transformer is low as appeared in the figure, however it
increment to a steady incentive as it gets steady.
- Then again the chart of the regulation is diminishing, also, it gets to the base
an incentive after short little time.
- For a decent transformer productivity ought to be high and on the other
regulation control to be little.
- The drawing of the equivalent impedance diagram was done using
calculated reactance in per unit.
16. CONCLUSION
To conclude, the power systems component were analysis using the Per Unit
systems and the manual calculations were compared with results simulated in
Matlab and Simscape Power Systems as displayed in the result section. In the
underlying state, the efficiency of a transformer is low as appeared in the figure,
however it increment to a steady incentive as it gets steady. Then again the chart
of the regulation is diminishing, also, it gets to the base an incentive after short
little time. So we can conclude that for a decent transformer productivity ought to
be high and on the other regulation control ought to be little.