Week 01- Introducing MATLAB and SIMULINK

1.Identify the tools and components in MATLAB and Simulink

Introduction

MATLAB (Matrix Laboratory) and Simulink are powerful software tools developed by MathWorks, widely used for mathematical computing, algorithm development, and system simulation.

MATLAB is a high-level programming language and environment designed for numerical computation, data analysis, and visualization. It provides a versatile platform for solving complex mathematical problems, developing algorithms, and creating interactive graphics. Its extensive libraries and toolboxes enable users to perform tasks ranging from simple calculations to advanced data analysis and modeling.

Simulink, an extension of MATLAB, offers a graphical environment for modeling, simulating, and analyzing dynamic systems. It allows users to build complex simulations through a user-friendly block diagram interface, making it ideal for designing and testing control systems, signal processing, and other engineering applications. Simulink’s integration with MATLAB enhances its functionality, providing a seamless workflow for simulation and code generation.

Together, MATLAB and Simulink are essential tools for engineers, scientists, and researchers, facilitating the development of innovative solutions and advancements across various fields, including robotics, aerospace, automotive, and biomedical engineering.

Sample Script of a MATLAB Project

Week 01 Learnings

1.Identify the tools and components in MATLAB and Simulink

Preview of MATLAB Live Script

Preview of MATLAB Simulink

The Live Script Editor in MATLAB provides an interactive environment for creating and sharing rich scripts that combine code, output, and formatted text. It allows users to document their analysis and visualization tasks dynamically, making it easier to present results and insights. The editor supports live code execution, interactive controls, and embedded graphics, enhancing productivity and clarity in technical reporting.

Simulink, integrated with MATLAB, enables users to model, simulate, and analyze complex systems through a graphical block diagram interface. It simplifies the design of dynamic systems by providing pre-built blocks for various components and functionalities. Simulink’s intuitive drag-and-drop interface, coupled with MATLAB’s computational power, facilitates the efficient development and testing of control systems, signal processing applications, and other engineering solutions.

2.Activites

Define the Matrix

Define the variable

Get the matrix

Counts the number of values

To select only the values in the first column

To select only the values in the first row

to get the inverse of the matrix

the eigenvectors of the matrix

Size of the matrix

Length of the matrix

ax2 + bx + c type equation

Define C (a variable to the Equation)

Preview of the variable C

find the roots

find the real numbers (method 01)

find the real numbers (method 02)

zero-pole-gain (ZPK)

Define the sys variables

sys function

Define the sys1 variables

sys1 function

Series of sys and sys1

Parallel of sys and sys1

Time Transfer Function

Define numerator and denominator

Preview of numerator and denominator

Time transfer function

zeros of sys and roots of M are same

poles of sys and roots of Z are same

pz map of sys

define sys,sys2 and sys3

feedback of sys and 1

feedback of sys and sys2

pzmap(feedback(sys,sys2))

pzmap(feedback(sys3,sys2))

define tf2

step plot of tf2

using the hold on and off for get more than one plot in same graph

first enter the first graph equation
type hold on
enter the second equation
hold off

Show the grid and legend

[y1,t1] = step(sys3); and plot the [t1,y1]

plot(t1,y1,'r')

plot(t1,y1,'r-.')

plot(t1,y1,'b*')

xlabel("x") enter

ylabel("y") enter

title("test") enter

3.Conclusion

In conclusion, this practical session provided a comprehensive exploration of various MATLAB functionalities essential for system analysis and design. We gained valuable insights into different types of coding techniques used in MATLAB, including defining and manipulating matrices with precision.

We learned how to create and interpret zero-pole-gain (ZPK) representations and time transfer functions, which are crucial for analyzing and designing control systems. The practical session also covered plotting and visualizing data through various types of graphs, enabling us to effectively represent and interpret system behavior. Additionally, we practiced labeling graphs to enhance clarity and communication of results.

Overall, this hands-on experience has significantly deepened our understanding of MATLAB’s capabilities, equipping us with practical skills for modeling, analyzing, and visualizing dynamic systems.

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