The Complete MATLAB Course: MATLAB Simulink Mastering

Review Matlab software's wide applications across mechanics, aerospace, medical engineering, and science; learn about simulations, Simulink basics, toolboxes, and the ability to create custom toolboxes via university-driven extensions.

Simulink, a Matlab toolbox, uses graphical design and blocks to model, simulate, and analyze data, enabling dynamic electrical, mechanical, and control system simulations within Matlab.

Explore how inputs, processes, disturbances, and outputs define systems in MATLAB Simulink, distinguishing dynamic versus static, discrete versus continuous, and open-loop versus closed-loop configurations; learn about time-dependent and independent simulations.

Design a mathematical model of a real system and test it with a computer using simulation in MATLAB Simulink, gaining fault analysis without building or disturbing the system.

Learn to work with Simulink in MATLAB, create a simple model in a symbolic environment, and implement it while exploring the symbolics library browser and version differences.

Explore the library of elements in Simulink, from common blocks for diverse applications to specialized deep blocks, including fuzzy logic control systems and communication systems.

explore ready-made MATLAB Simulink samples and demos, analyze how they’re built, and adapt or modify them in your project to save time and improve simulations.

Compare MATLAB Simulink 2017 with 2015, noting the project-oriented menu, updated libraries and blocks, and new templates; learn how to access libraries and examples across versions.

Explore practical Matlab Simulink simulations of mathematical equations using blocks, integrators, sine and cos functions, and various sources for time-based signals.

Learn how to modify block information in simulink by defining values in the workspace, in an m-file, or in block properties, with callbacks and initial conditions.

Learn to customize Simulink blocks by resizing, renaming, and formatting, including font, color, and background changes. Manage block display, rotation, masking, and priority to control block connections and execution.

Explore the commonly used Simulink blocks, including multiplication, division, gain, and matrix operations, and learn to create and select bus signals with bus creator and bus selector.

Explore the commonly used section library in MATLAB Simulink, including blocks for signals, thresholds, comparisons, and logic, and how to work with sine inputs, matrices, and complex numbers in simulations.

Explore the continuous section blocks in Matlab, learning how to use integrator blocks, time delay, transfer functions, initial conditions, and saturation to model and simulate dynamic systems.

Introduce source section blocks and locks for displaying outputs and simulation control. Use a terminator to keep unused signals and transfer data to the MATLAB workspace for xy graph.

Explore sink section blocks in Simulink, including signal generator options (sawtooth, square, random), pulse generation, and the signal builder for custom signals and simulations.

Explore signals in Simulink, covering dimensions, types, and how signals connect and transfer between blocks. Learn to treat signals as logical inputs and outputs across a model.

Learn to connect signals between origin and destination blocks in Simulink, troubleshoot red lines, view signal information, and manage signal types such as constants and complex numbers for proper transfer.

Explore how signal dimensions in Simulink affect display, data types, and matrix operations, and learn to interpret four-column, one-row signals, initial conditions, and time-based data in models.

Explore signal-related blocks in simulink, including selectors to separate large data signals, and subsystems used to create subsystem signals.

Explore signals and blocks in Simulink by highlighting signals to source, removing highlights, and double-clicking to recall, while adjusting font size and signal properties to limit data.

Explore the subsystems concept, learn how to create subsystems and symbols, and build a mask for soft systems that updates with the mask icon.

Create and customize masks for subsystems in Simulink, learn how to convert a model to a subsystem, and adjust mask parameters, initialization, and block options.

Learn to solve mathematical equations in MATLAB Simulink using the zero solver named Zero and the math operation library, including single-variable and multi-variable problems set to zero.

Explore solving high-level equations in MATLAB Simulink by building and simulating signal paths with power, sum, and multiplier blocks, adjusting signs, and verifying outputs.

Learn to solve nonlinear equations by applying trigonometric identities and substitutions, transforming complex parts into simpler forms for quick, accurate solutions.

Solve equations with multiple variables using algebraic constraints and R&D parameters in a single project, defining C1, Z2, and Z3 as unknowns across four equations.

Explore multiple modeling approaches in Simulink, including state-space and transfer function representations, and map zeros and poles to design and simulate dynamic systems.

Learn to model and simulate a system using standard blocks, including transfer function blocks, and analyze the response of a previously shown model in Simulink.

Learn to simulate a system using a transfer function model in MATLAB Simulink, employing the transfer function block to estimate integration and observe the system's output.

Master state space model in MATLAB and learn to simulate a system, set the initial condition, and relate it to a transfer function.

Learn to set zeros, poles, and gain in MATLAB to model transfer functions, either with or without blocks, and understand zero-pole representations in Simulink.

Explore how to design and implement PID controllers and related control strategies in a simulated system, using transfer functions, feedback, and basic controller design.

Explore different control libraries in Simulink, including the control system toolbox and other toolboxes, and learn to identify, model, and simulate projects such as a magnetic ball system.

Explore continuous, discrete, and hybrid system simulation in MATLAB Simulink, using discrete blocks, delays, transfer functions, and state-space models to combine sampling methods and validate results.