Matlab program to design a 30 HP,440 V, 50 Hz, Delta connected Induction Motor

This post will teach you how to ulitize Matlab in Induction Motor design, this is real time engineering application example: Problem statement: Design a 30HP, 3 phase, 440V, 900 r.p.m, 50Hz, delta connected squirrel cage induction motor. Assume specific electric loading 25000, specific magnetic loading .46 Wb full load effeciency 85% power factor = .9 calculate the following i) Stator core dimension D and L ii) Number of stator slots and winding turns Matlab program: %Matlab program to design squirrel cage induction motor clc; clear all; Po = 30*.746; %kw Vin = 440; N = 900; Ns = N/60; f = 50; Bav = .46; pf = 0.9; eff = 0.85; ac = 25000; Kws = .955; phase = 3; %rating in kVA Q = Po/(eff*pf); Kw = .9; fprintf('\nProgram to design squirrel cage induction motor'); fprintf('\n_______________________'); Co = 1.11*pi*pi*Bav*ac*Kw*(10^-3); %number of poles pole = (2*f)/Ns; %Q = Co*Ns*D2L disp('Input power or rating power = '); disp(Q); D2L = Q/(Co*Ns); %for good overall design %L/tow = 1 %L*pole/pi*D D3 = (Q*pole)/(Co*Ns*pi); D = D3^(1/3); disp('Hence Diameter D = '); disp(D); disp('Hence Length L = '); L = pi*D/(pole); disp(L); %peripheral speed Va Va = pi*D*Ns; disp('Peripheral speed = '); disp(Va); if(Va<30) fprintf('\nAs Peripheral speed is less than 30m/secs so dimensions are permissable'); else fprintf('\nAs Peripheral speed is not less than 30m/sec the dimensions are not mpermissabel. But still the dimensions will be'); end phim = Bav*pi*D*L/pole; fprintf('\nFlux density phim = '); disp(phim); %number of stator turns Ts Ts = Vin/(4.44*f*phim*Kws); fprintf('\nNumber of stator turns Ts = '); disp(round(Ts)); %total number of stator slot per phase per pole Ss Ss = 3*pole*phase; fprintf('\nTotal number of stator slot per phase per pole Ss'); disp(Ss); fprintf('\nSlot pitch Yss = '); Yss = pi*D/Ss; disp(Yss); Zss = 6*round(Ts); fprintf('\nTotal Coonductors Zss = '); disp(Zss); fprintf('\nNumber of Slots = '); noofslots = Zss/Ss; disp(noofslots); fprintf('\n——————'); fprintf('\nCreated By A K Tyagi'); Program Output: Program to design squirrel cage induction motor _______________________Input power or rating power = 29.2549 Hence Diameter D = 0.3317 Hence Length L = 0.1563 Peripheral speed = 15.6318 As Peripheral speed is less than 30m/secs so dimensions are permissable Flux density phim = 0.0112 Number of stator turns Ts = 185 Total number of stator slot per phase per pole Ss 60 Slot pitch Yss = 0.0174 Total Coonductors Zss = 1110 Number of Slots = 18.5000 —————— Created By A K Tyagi>>

Wanna learn Matlab, bored from fake Matlab courses

If you really want to learn and admire the features of Matlab and are bored from the fake courses of Matlab which will never teach you about the fundamentals of Matlab join the following course. 40% ENGINEERS I meet who claim they know Matlab do not even know the fundamentals of Matlab programming. Matlab is mastered by me and I always proud of imparting my knowledge to the genuine seekers. Good Luck!!! MATLAB/SIMULINK Course structure Complete course on MATLAB Duration: 56 Hrs or 6 weeks (1.5 month) Coverage: Session 1 to 9 Fees: Rs 12,000/- Session # Title of session Brief Description Expected Duration (hrs) Sess.-1 An overview of MATLAB This session devoted to MATLAB basics like various types of windows, symbols, commonly used commands, various Formats available, mediocre arithmetic operations along with their operations, engineering programming approach with programs and simple programming exercises follows. 6(4 for illustrations & 2 for discussions with students) Sess.- 2 Intro to MATLAB programming Review of session 1 with few more illustrations and exercises so as to build up a robust foundation for a naïve programmer along with a practice session of 4-6 hrs 3 to 4 depending on the understanding of the students and a practice session of 4-6 hrs Sess.- 3 Fundamentals of MATLAB programming In this session fundamentals required for programming like variables, useful commands, arrays & their syntax matrices, arithmetic operations, relational operators, logical operators & operator precedence will be demonstrated. Further we will discuss about MATLAB graphics (2D & 3D plots), Branching & looping functions, Input & Output functions along with detailed programming problems. This session is again followed by a practice session & illustrations so as to make a good foundation for coding. 8 (4 for discussions and illustrations & 4 for programming exercises) Sess.- 4 Numeric cells & Structured Arrays This session deals with Vectors, creating Arrays & Matrices, array addressing, multi-dimensional arrays, array operations, special Matrices, polynomials, structure functions & illustrative examples 4 Sess. 5 Programming structure In this session algorithms & control structures, structured programming, step for developing a computer solution, Documenting with charts, flow chart representation for various statements, pseudo codes, finding bugs, operators, strings and conditional statements are discussed. 4 Sess. 6 Fundamentals of Simulink This session is devoted to fundamentals of Simulink and covers: Introduction to Simulink, frequently used blocks, Configuration parameters, various blocks and their description, power system simulation blockset and simulation projects. 6 (4 for discussion and 2 for illustration) Sess. 7 Applications of Basic Electrical Engineering Elementary definitions, Basic waveforms, average, rms & peak values, Ohm’s law, KCL, KVL, Dependant sources, Series/parallel circuits, Superposition, Reciprocity, Thevenin’s, Maximum power transfer theorems, Types of powers and Simulation projects 6 Sess. 8 Simulation of Rectifiers This session deals with power electronic Rectifiers. It contains introduction, performance parameters, controlled & uncontrolled switches, different types of rectifiers with various loads and their analysis and Simulation projects. 6 Sess. 9 Review & brainstorming This review and brainstorming session for setting up the things learned by you so far. One or two projects might be discussed. 2 For further enquires contact 9557069448, tyagiagam@gmail.com Visit: agamtyagi.blogspot.com regularly Following are the snaps of my active Matlab Learning centre:

Program for subplots of flowers in Matlab

clf n=4; n2=n*n; % for a 2-by-2 graphics window theta=linspace(0,2*pi,200); for j=1:n2 r=sqrt(abs(2*sin(j*theta))); plotnum=[int2str(n),',',int2str(n),',',int2str(j)]; eval(['subplot(',plotnum,')',',',' polar(theta,r)']); end

Simple Program to transfer data in Matlab by Com ports (USB) serially

%% Create a serial object CALLED Board board = serial('COM8', 'BaudRate', 96000, 'DataBits',8); fopen(board); %This code will open and connect to COM8 with a speed of 96000 baud and %8 bits of data will be transferred to the deivice connected to the com 8 % port % you can also use fprintf command to transfer the data serially

Matlab program to find prime numbers: first hundered if n = 100

n = 103; numbers = 2: n; primes = []; for i = 1: length(numbers) if ~ numbers(i) == 0 for j = i+1: length(numbers) if rem(numbers(j), numbers(i)) == 0 numbers(j) = 0 end end end if ~ numbers(i) == 0 primes(length(primes) + 1) = numbers(i) end end primes

Plotting complex polar graph in MATLAB

Numerical#2 A complex number z can be represented as z = rejθ. The nth power of the complex number is given as Zn = rn ejnθ. If r = 1.2 and θ = 10˚, use polar plot to plot |zn| versus nθ for n = 1 to 36. Solution: % polar plot of z r = 1.2; theta = 10*pi/180; angle = 0:theta:36*theta; mag = r.^(angle/theta); polar(angle,mag, 'g*-') grid title('Polar Plot') The output of the program is shown below in figure:

To plot V(t) and I(t) for an electrical RL circuit: Matlab Program

Numerical # 1 For an R-L circuit, the voltage v(t ) and current i(t ) are given as V(t) = 10cos(377t); i(t) = 5 cos(377t+60˚) Sketch v(t ) and i(t ) for t = 0 to 20 milliseconds. Solution MATLAB Script % RL circuit % current i(t) and voltage v(t) are generated; t is time t = 0:1e-3:20e-3; v = 10*cos(377*t); a_rad = (60*pi/180); % angle in radians i = 5*cos(377*t + a_rad); plot(t,v,'r*',t,i,'go') title('Voltage and Current of an RL circuit') xlabel('Sec') ylabel('Voltage(V) and Current(mA)') text(0.003, 1.5, 'v(t)'); text(0.009,2, 'i(t)') The output of program can be seen in figure below

MATLAB program to compute the back EMF and armature current of a DC Motor

clc; clear all; P = input('Number of poles are: '); Phi = input('Flux per pole in Wb is: '); Z = input('Total number of armature conductors are: '); N = input('Armature speed in rpm is: '); V = input('Supply voltage in volts is: '); Ra = input('Armature resistance in Ohms is: '); W = input('1 for lap wining and 2 for wave winding: '); if W == 1 Eb = (Phi * N * Z) / 60; end if W == 2 Eb = (P * Phi * N * Z)/120; end Ia = (V - Eb)/ Ra; disp('Back EMF developed in the motor in volts is:'), Eb disp('Armature current in A is: '); Ia

Response of RL and RC circuits plot

% To plot response of RL and RC circuits % R = 10, L = 20e-3 H for RL circuit V = 100; % Volts R = 10; % Ohms L = 20e-3; % Henry Im = V/R; to = L/R; t = 0:10e-6:0.02; i = Im*(1-exp(-t/to)); figure(1) plot(t,i) title('Response of R-L circuit') xlabel('T (sec)'), ylabel('i(t)') % R = 100, C = 20e-6 F for RC circuit R = 100; C = 200e-4; Vm = V; to = 1/(R*C) t = 0:10e-6:6; v = Vm*(1-exp(-t/to)); figure(2) plot(t,v) title('Response of R-C circuit') xlabel('T (sec)'), ylabel('v(t)')

Series and parallel resonance response

% This program plot a graph of frequency vs impedance in case of series % resonance clc; clear all; f = 100:1:400; L = 6.34e-3; C = 100e-6; R = 100; XL = 2*pi*f*L; XC = 1./(2*pi*f*C); Z = (R^2 + (XL - XC).^2).^0.5; figure(1) plot(f,Z) title('\bf Impedance vs frequency plot for series resonance'); xlabel('\bf Supply frequency in Hz'); ylabel('\bf Impedance in Ohms'); Z = 1./(1./XL+1./XC); figure(2) plot(f,Z) title('\bf Impedance vs frequency plot for parallel resonance'); xlabel('\bf Supply frequency in Hz'); ylabel('\bf Impedance in Ohms');

Design of Seven step multi level inverter

The concept of utilizing multiple small voltage levels to perform power conversion was patented by an MIT researcher over twenty years ago. Advantages of this multilevel approach include good power quality, good electromagnetic compatibility (EMC), low switching losses, and high voltage capability. The main disadvantages of this technique are that a larger number of switching semiconductors are required for lower-voltage systems and the small voltage steps must be supplied on the dc side either by a capacitor bank or isolated voltage sources. The first topology introduced was the series H-bridge design. This was followed by the diode clamped converter which utilized a bank of series capacitors. A later invention detailed the flying capacitor design in which the capacitors were floating rather than series-connected. Another multilevel design involves parallel connection of inverter phases through inter-phase reactors

. In this design, the semiconductors block the entire dc voltage, but share the load current. Several combinational designs have also emergedsome involving cascading the fundamental topologies. These designs can create higher power quality for a given number of semiconductor devices than the fundamental topologies alone due to a multiplying effect of the number of levels.

Design of Buck converter by static diode model for 12 V to 5 V 100 W load

Design of DC power supply by diode capacitor bridge

This diode capacitor bridge is widely used for power supplies intended to function over extreme input voltage ranges. In this circuit there are only three valid configurations. When the voltage is first applied diode D1 quickly becomes ON. Assume that the initial capacitor voltages are zero. Since the capacitor voltage is initially zero diode D1 and C2 conducts and supply current to the load. Also the current flows through C1 as when D1 is ON Vin is identical to Vc1. Since the RC time constant is very slow compared to the sinusoidal changes in input supply C2 will not charge up much. As long as D1 is ON Vc1 must track Vin. This configuration will remain valid shortly after Vin has peaked.  Simulation of this configuration is carried out in MATLAB and the output load voltage and capacitors current as observed are shown in the figure. 

Rectified output for half and full wave by Matlab code

inline and ezplot functions elaborated

You can simply plot the function by using inline and ezplot command in the following way:

> fcn = inline('exp(-0.2*t).*sin(200*t+pi/20)','t')

fcn =

     Inline function:

     fcn(t) = exp(-0.2*t).*sin(200*t+pi/20)

>> fcn(0:10e-4:0.4);

>> ezplot(fcn)

time t array can be varied and again a new c=plot can be achieved

Matlab code for switch case function: Conversion of units of length

% Matlab program to demonstrate switch case function

x = 3.0;               % numeric variable for length
units = 'cm';         % string variable for unit
switch     units
    case    {'in','inch'}      % case 1 if unit is inch
           y = 2.54*x;        % converts to centimeters
          disp  ([num2str(x)  '   ' units ' converted to cm is :' num2str(y)])
            %  disp is used to print pretty in the command window
            %  in the above a string vector is being printed
     case   {'m','meter'}    % case 2 unit is meter
           y = x*100;        % converts to centimeters
           disp  ([num2str(x)  '   ' units ' converted to cm is :' num2str(y)])
     case   { 'millimeter','mm'} % case 3 unit is millimeter
           y = x/10;
          disp  ([num2str(x)  '   ' units ' converted to cm is :' num2str(y)])
    case {'cm','centimeter'}     % case 4 unit is centimeter
          y = x;
          disp  ([num2str(x)  '   ' units ' converted to cm is :' num2str(y)])
    otherwise                    % for all other cases
         disp    (['unknown units:' units])
         y = nan;  % not a number
end

Three Phase Diode Rectifier

Prosthetic hands for manipulating objects for disabled

In this project, students learn how prostheses that use robotic technology can improve the lives of people with disabilities. In the laboratory, the students can use Lego Mindstorms NXT kits to create an artificial arm or hand that can lift small objects, such as a coffee cup. In the process, students discover and explore the following concepts and ideas: Hooke's Law, hysteresis, Newton's Second Law, accuracy and precision, rapid prototyping, and the relationship between the voltage applied to a motor and its speed.

Ant Colony Optimization (ACO) for engineering research and projects

Ant colonies, and more generally social insect societies, are distributed systems that, in spite of the simplicity of their individuals, present a highly structured social organization. As a result of this organization, ant colonies can accomplish complex tasks that in some cases far exceed the individual capabilities of a single ant. The field of ‘‘ant algorithms’’ studies models derived from the observation of real ants’ behavior, and uses these models as a source of inspiration for the design of novel algorithms for the solution of optimization and distributed control problems. The main idea is that the self-organizing principles which allow the highly coordinated behavior of real ants can be exploited to coordinate populations of artificial agents that collaborate to solve computational problems. Several different aspects of the behavior of ant colonies have inspired different kinds of ant algorithms. Examples are foraging, division of labor, brood sorting, and cooperative transport. In all these examples, ants coordinate their activities via stigmergy, a form of indirect communication mediated by modifications of the environment. For example, a foraging ant deposits a chemical on the ground which increases the probability that other ants will follow the same path. Biologists have shown that many colony-level behaviors observed in social insects can be explained via rather simple models in which only stigmergic communication is present. In other words, biologists have shown that it is often su‰cient to consider stigmergic, indirect communication to explain how social insects can achieve self-organization. The idea behind ant algorithms is then to use a form of artificial stigmergy to coordinate societies of artificial agents.

This technique of ant communication for finding the shortest available path between their nest and the food source by depositing pheromones can be applied for optimization various engineering problems and there comparison with other conventional techniques. 

Induction motor drive by 3-level PWM inverter by v/f method

Be it domestic application or industry, motion control is required everywhere. The systems that are employed for this purpose are called drives. Such a system, if makes use of electric motors is known as an electrical drive. In electrical drives, use of various sensors and control algorithms is done to control the speed of the motor using suitable speed control methods. Earlier only dc motors were employed for drives requiring variable speeds due to ease of their speed control methods. The conventional methods of speed control of an induction motor were either too expensive or too inefficient thus restricting their application to only constant speed drives. However, modern trends and development of speed control methods of an induction motor have increased the use of induction motors in electrical drives extensively. In this project, we will study the various methods of speed control of a 3-ph induction motor and compared them using their Torque-Speed characteristics. Also the transients during the starting of a 3-ph induction motor will be studied using MATLAB Simulink and the effects of various parameters such as rotor and stator resistances and inductances well be analyzed

Project: Matlab/Simulink modeling of PV cell and their comparative study

Solar energy has a major role in renewable energy resources. Solar Cell as a basement of solar system has attracted lots of research. To conduct a study about solar energy system, an authenticated model is required. Diode base PV models are widely used by researchers. These models are classified based on the number of diodes used in them. Single and two-diode models are well studied. Single-diode models may have two, three or four elements. In this project, these solar cell models are examined and the simulation results are compared to each other. All PV models are re-designed in the Matlab/Simulink software and they examined by certain test conditions and parameters. This project will provide comparative studies of these models and it tries to compare the simulation results with manufacturer’s data sheet to investigate model validity and accuracy.

Power Electronics Devices & converters A K Tyagi

Cycloconverters or frequency changers

MATLAB & Simulink Based Books - Optical Wireless Communications: System and Channel Modelling with MATLAB - MathWorks India

Written for undergraduate and graduate students as well as researchers and professional engineers,Optical Wireless Communications: System and Channel Modelling with MATLAB provides comprehensive coverage of optical wireless communications. The book discusses both indoor and outdoor environments and the different factors affecting system performance. Topics include optical wireless communication systems, optical sources and detectors, channel modeling and modulation techniques. 

MATLAB & Simulink Based Books - Optical Wireless Communications: System and Channel Modelling with MATLAB - MathWorks India

Project ideas: Design and analysis of three phase cycloconverter for variable load

The objective of this study is to observe the correlations between variable operating conditions and power quality parameters for a three-phase to single-phase cycloconverter. The cycloconverter is examined in its most straightforward form without additional output filters or elaborate control methods. Variable operating conditions include input frequency, output frequency, and resistive load size. The power quality parameters of interest are power factor, input current total harmonic distortion (THD), output voltage THD, and efficiency. The scope of the project includes analytical calculations, Matlab/Simulink simulations, and /or hardware implementation. The results show that output frequency has minimal effect on power quality. Total harmonic distortion undesirably peaks at a combination of low input frequency and high output frequency. Extrapolations can be made for the cycloconverter operating at different frequencies and loads based on the trends observed within the test matrix. This can be a good design and innovative exercise to perform.

Student Project: Power Quality Improvement by DC Drives

Power Quality (PQ) has become an important topic of discussion and research, especially in a deregulated environment. As per IEEE 519 std. these parameters of power quality measurement, are four in number, of which Total Harmonic Distortion is most widely used. Semiconductor switching devices in Power Electronics which are generally used in converter circuits produce significant harmonic voltages as they chop voltage waveforms during the transition between the conducting and cutoff stages. The diode bridge rectifiers/converters are considered as a major contributor to the power system harmonics and the consequences are varying from components overheating to communication

interference. This project links the field of electrical power conversion and electrical drives (DC), where these power converters find applications. Electric drives play an important role in industry as well as our day-to-day life. They are use the electrical power input and provide mechanical work as output. This project can be well designed and simulated in MATLAB environment. 

Student Project: Energy generation by excercise

In this project, students learn about the energy generation and usage. Emphasis is placed on potential sources of renewable energy, and on how power demands vary from country to country. The students learn how energy is measured, and experiment with generating and storing energy themselves, using an AC or DC generator connected to a bicycle and lead-acid batteries. They can measure how long common household appliances can be run on the stored energy, and in the process gain a better understanding of their own personal energy usage. Design of different energy efficient converters can be undertaken in this project. 

Student Project: Energy Efficient Electric Vechile

In this project, the students learn how brushless DC motors have made personal electric vehicles (PEVs) possible, and calculate how much using a PEV instead of an automobile for some of their daily driving can impact their production of carbon dioxide, based on United States driving patterns. In the laboratory, students build a brushless DC motor using three different control methods, based on a reed switch, a Hall effect sensor, and optoelectronics, respectively. In the process, students learn about motors, and compare the components used for control in terms of their reliability. 

Image processing by changing RBG count

Maximum power transfer theorem MATLAB

SCR Rectifier Full wave

How to Solar Power Your Home / House #1 - On Grid vs Off Grid

Mc Murray inverter Simulation

Special Matrix plots! : Hibert, Magic, Pascal, Toeplitz, Vandermonde, Wilkinsons just enter command and view it

This just time pass to learn some of the special matrices of Algebra, code follows:

In linear algebra, a Hilbert matrix, introduced by Hilbert (1894), is a square matrix with entries being the unit fractions

For example, this is the 10 × 10 Hilbert matrix:

hilb(10); % Hibert Matrix

h = hilb(10);

plot(h)

title('Hilbert Matix')

axis off

hi = invhilb(10) % Inverse Hilbert matrix

hi =

   1.0e+12 *

    0.0000   -0.0000    0.0000   -0.0000    0.0000   -0.0000    0.0000   -0.0000    0.0000   -0.0000

   -0.0000    0.0000   -0.0000    0.0000   -0.0002    0.0005   -0.0008    0.0008   -0.0004    0.0001

    0.0000   -0.0000    0.0001   -0.0010    0.0043   -0.0112    0.0178   -0.0166    0.0085   -0.0018

   -0.0000    0.0000   -0.0010    0.0082   -0.0379    0.1010   -0.1616    0.1529   -0.0788    0.0171

    0.0000   -0.0002    0.0043   -0.0379    0.1768   -0.4772    0.7713   -0.7359    0.3821   -0.0832

   -0.0000    0.0005   -0.0112    0.1010   -0.4772    1.3015   -2.1210    2.0378   -1.0644    0.2330

    0.0000   -0.0008    0.0178   -0.1616    0.7713   -2.1210    3.4807   -3.3640    1.7661   -0.3884

   -0.0000    0.0008   -0.0166    0.1529   -0.7359    2.0378   -3.3640    3.2679   -1.7233    0.3804

    0.0000   -0.0004    0.0085   -0.0788    0.3821   -1.0644    1.7661   -1.7233    0.9123   -0.2021

   -0.0000    0.0001   -0.0018    0.0171   -0.0832    0.2330   -0.3884    0.3804   -0.2021    0.0449

plot(hi)

title('Inverse Hilbert Matix')

axis off

%In recreational mathematics, a magic square is an arrangement of numbers (usually integers) in %a square grid, where the numbers in each row, and in each column, and the numbers in the forward %and backward main diagonals, all add up to the same number. A magic square has the same number %of rows as it has columns, and in conventional math notation, "n" stands for the number of rows (and %columns) it has. Thus, a magic square always contains n² numbers, and its size (the number of rows %[and columns] it has) is described as being "of order n". A magic square that contains the integers %from 1 to n² is called a normal magic square.

m = magic(10)% Magic Matrix

m =

    92    99     1     8    15    67    74    51    58    40

    98    80     7    14    16    73    55    57    64    41

     4    81    88    20    22    54    56    63    70    47

    85    87    19    21     3    60    62    69    71    28

    86    93    25     2     9    61    68    75    52    34

    17    24    76    83    90    42    49    26    33    65

    23     5    82    89    91    48    30    32    39    66

    79     6    13    95    97    29    31    38    45    72

    10    12    94    96    78    35    37    44    46    53

    11    18   100    77    84    36    43    50    27    59

plot(m)

plot(m)

title('Magic Matrix')

axis off

In mathematics, particularly matrix theory and combinatory, the Pascal matrix is an infinite matrix containing the binomial coefficients as its elements. There are three ways to achieve this: as either an upper-triangular matrix, a lower-triangular matrix, or asymmetric matrix

pascal(10) % Pascal Matrix

ans =

           1           1           1           1           1           1           1           1           1           1

           1           2           3           4           5           6           7           8           9          10

           1           3           6          10          15          21          28          36          45          55

           1           4          10          20          35          56          84         120         165         220

           1           5          15          35          70         126         210         330         495         715

           1           6          21          56         126         252         462         792        1287        2002

           1           7          28          84         210         462         924        1716        3003        5005

           1           8          36         120         330         792        1716        3432        6435       11440

           1           9          45         165         495        1287        3003        6435       12870       24310

           1          10          55         220         715        2002        5005       11440       24310       48620

plot(ans)

title('Pascal Matrix')

axis off

%A matrix equation of the form

%

%is called a Toeplitz system if A is a Toeplitz matrix. If A is an   Toeplitz matrix, then the %system has only 2n−1 degrees of freedom, rather than n². We might therefore expect that the %solution of a Toeplitz system would be easier, and indeed that is the case.

t = toeplitz(10) % Toeplitz Matrix

t =

    10

A Vandermonde matrix is a type of matrix that arises in the polynomial least squares fitting, Lagrange interpolating polynomials (Hoffman and Kunze p. 114), and the reconstruction of a statistical distribution from the distribution's moments

v = vander(10) % Vandermonde Matrix

v =

     1

In linear algebra, Wilkinson matrices are symmetric, tridiagonal, order-N matrices with pairs of nearly, but not exactly, equal eigenvalues. It is named after the British mathematician James H. Wilkinson

w = wilkinson(10) % Wilkinsons eigen value test matrix

w =

    4.5000    1.0000         0         0         0         0         0         0         0         0

    1.0000    3.5000    1.0000         0         0         0         0         0         0         0

         0    1.0000    2.5000    1.0000         0         0         0         0         0         0

         0         0    1.0000    1.5000    1.0000         0         0         0         0         0

         0         0         0    1.0000    0.5000    1.0000         0         0         0         0

         0         0         0         0    1.0000    0.5000    1.0000         0         0         0

         0         0         0         0         0    1.0000    1.5000    1.0000         0         0

         0         0         0         0         0         0    1.0000    2.5000    1.0000         0

         0         0         0         0         0         0         0    1.0000    3.5000    1.0000

         0         0         0         0         0         0         0         0    1.0000    4.5000

plot(w)

title('Wilkinson Matrix')

axis off

Conserve water the magical gift of Nature

Matlab and Simulink for Engineers, Book actual snap shots of 3 rd impression: What is new?

Introduction to Matlab and applications

Matlab Graphics: Amazing hats!! created in Matlab using colormap

MTech projects titles for engineering students

1.     Modeling and Simulation of standalone Photovoltaic system for onsite power generation.

2.     Design and Simulation of Matrix Converter based PWM drive for aircraft actuator.

3.     Analysis and comparative performance study of matrix converter and three level inverter.

4.     Modeling and Simulation of Unified power controller for power quality improvement.

5.     Analysis and study of distributed generation system for different fault conditions using MATLAB.

6.     Analysis and design of passive filters for power quality improvement.

7.     Modeling and design of SVPWM based speed control of Induction Motor using V/F control.

8.     Modeling and design of solar panel for different irradiation pattern of sun using Matlab.

9.     Modeling and design of Wind based system to find the power response of a wind turbine for variable wind speeds.

10. Speed control of three phase Induction Motor.

Contact: 9557069448, tyagiagam@gmail.com