Simulink Control Engineering Tutorial

From Zero to Embedded Code Deployment — 25 Hands-On Lessons
Classical, Modern, Robust, Nonlinear, MPC, Adaptive, Fuzzy, Physical Modeling, and Code Generation

中文版请见 README.md

Preview
Quick Start
Prerequisites
Tutorial Overview
Learning Path
What You'll Learn
Project Structure
Companion Projects
Contributing
License

Preview

All figures auto-generated by run_all_tutorials. See docs/images for the full set.

PID Control (t05)	LQR Optimal Control (t10)

Kalman Filter (t12)	PMSM FOC (t14)

Quick Start

Step 1: Clone

git clone https://github.com/xingd5478-ctrl/simulink-control-tutorial.git

Step 2: Check your environment

In MATLAB, navigate to the project folder and run:

>> check_setup

Step 3: Start learning

>> t00_main_guide            % Course overview (25 lessons)
>> t01_signal_basics         % Lesson 1: Sine wave + Gain + Scope

Step 4: Follow the learning path

% Phase 1 (t01-t08) — Simulink fundamentals, no extra toolboxes needed
% Phase 2 (t16, t17, t22) — Classical control design
% Phase 3 (t09-t12) — Modern control theory
% Phase 4 (t18-t21, t23, t24) — Advanced control topics
% Phase 5 (t13, t14, t25, t15) — Applications & deployment

% Or run everything at once:
>> run_all_tutorials

Each script auto-creates a Simulink model (.slx) → configures blocks → runs simulation → generates result plots. No manual model-building required.

After each lesson

Double-click the Scope block — view the waveform
Double-click other blocks — see how parameters are set
Tweak a parameter — change Gain from 2 to 5, re-run, observe the change
Look at the MATLAB Figure — comparison plots help you understand concepts

Prerequisites

Dependency	Notes	Phase
MATLAB R2020a+	Core runtime	All
Simulink	Model building and simulation	All
Control System Toolbox	State-space, LQR, Kalman, freq analysis	Phase 2-5
Robust Control Toolbox	H∞ / μ analysis	t19 (optional)
Model Predictive Control Toolbox	MPC design	t20 (optional)
Fuzzy Logic Toolbox	Fuzzy inference system	t24 (optional)
Simscape	Physical modeling	t25 (optional)

Beginner tip: t01-t08 need only MATLAB + Simulink. Run check_setup to verify your environment.

FAQ

Q: I have zero control theory background. Can I follow?

Yes. Phase 1 (t01-t08) teaches only Simulink operations, no control theory. Later lessons explain control concepts as needed.

Q: "Undefined function or variable" error?

Make sure MATLAB's Current Folder is the project root (simulink-control-tutorial/). Use the folder panel in MATLAB to navigate there.

Q: No waveform in Scope?

Double-click the Scope block. If the line is flat, check the Step block's Step time parameter — it jumps at 0.5s, not 0s.

Q: Too many model windows open?

>> bdclose all     % Close all Simulink models
>> close all       % Close all Figures

Q: How do I regenerate a tutorial model?

Simply re-run the script — it overwrites the old .slx:

>> t05_pid_control

Tutorial Overview

25 lessons, 5 phases — progressive learning path from fundamentals to industrial applications.

Phase 1 — Simulink Fundamentals (t01-t08)

#	Tutorial	Content	Model
t01	Signal Basics	Signals, gain blocks, scopes	✅
t02	Math Operations	Sum, product, Mux/Demux routing	✅
t03	First-Order Systems	Transfer functions, time constants	✅
t04	Second-Order Systems	Damping ratio, overshoot, natural frequency	✅
t05	PID Control	P/I/D effects, feedback loop tuning	✅
t06	Sources & Sinks	Data import/export, signal generators	✅
t07	Subsystems	Hierarchical model packaging	✅
t08	Masking	Parameterized block design	✅

Phase 2 — Classical Control Design (t16, t17, t22)

#	Tutorial	Core Theory	Engineering Value
t16	Frequency Domain	Bode, Nyquist, Nichols, gain/phase margin	Stability analysis
t17	Lead-Lag Compensator	Lead/Lag compensation, frequency shaping	Classical control design
t22	Root Locus	rlocus(), pole trajectories, compensator design	Classical design visualization

Phase 3 — Modern Control Theory (t09-t12)

#	Tutorial	Core Theory	Engineering Value
t09	State-Space Models	ẋ=Ax+Bu, y=Cx+Du	Modern control foundation
t10	LQR Optimal Control	Pole placement, Riccati equation, Q/R tuning	MIMO system design
t11	State Observer	Luenberger Observer, duality, (A-LC)	Sensorless control
t12	Kalman Filter	lqe(), Q/R noise modeling, Luenberger comparison	Optimal estimation under noise

Phase 4 — Advanced Control Topics (t18-t21, t23, t24)

#	Tutorial	Core Theory	Engineering Value
t18	System Identification	Step response, least-squares, model validation	From data to transfer function
t19	H∞ Robust Control	Mixed sensitivity, hinfsyn, μ analysis	Optimal control under uncertainty
t20	MPC	Receding horizon, QP constraints, explicit MPC	Constrained multivariable control
t21	Sliding Mode Control	Sliding surface, chattering suppression, STSMC	Nonlinear robust control
t23	MRAC Adaptive Control	MIT rule, reference model, parameter adaptation	Online tuning for time-varying systems
t24	Fuzzy Logic Control	Sugeno FIS, membership functions, control surface	Model-free expert knowledge control

Phase 5 — Applications & Deployment (t13, t14, t25, t15)

#	Tutorial	Core Theory	Engineering Value
t13	DC Motor Control	Electromagnetic + mechanical coupling, cascaded PI, LQR	Actuator modeling
t14	PMSM + FOC	d-q transform, Clarke/Park, vector control	Brushless motor control
t25	Simscape Physical Modeling	Physical components, multi-domain, auto-derived equations	Formula-free modeling approach
t15	Code Generation	c2d discretization, dlqr, C code, FreeRTOS	Embedded deployment

Learning Path

Phase 1 (Basics)    Phase 2 (Classical)  Phase 3 (Modern)    Phase 4 (Advanced)   Phase 5 (Apps)
                                                                                
t01-t08 Basics ──→ t16 Freq Domain ──→ t09 State-Space ──→ t18 System ID ──→ t13 DC Motor
                     │                   │                   │                  │
                     ├── t17 Lead-Lag    ├── t10 LQR         ├── t19 H∞       ├── t14 FOC
                     │                   │                   │                  │
                     └── t22 Root Locus  ├── t11 Observer    ├── t20 MPC      ├── t25 Simscape
                                         │                   │                  │
                                         └── t12 Kalman      ├── t21 SMC       └── t15 Code Gen
                                                             │
                                                             ├── t23 MRAC
                                                             │
                                                             └── t24 Fuzzy

What You'll Learn

After completing all 25 lessons, you will be able to:

Derive state-space models from physical laws
Design LQR/Kalman optimal controllers and observers
Analyze stability in the frequency domain (Bode/Nyquist) and design compensators
Identify system models from experimental data
Handle parameter uncertainty with H∞ robust control
Design MPC controllers for constrained systems
Implement sliding mode control for nonlinear/high-disturbance systems
Analyze pole trajectories with root locus and design compensators
Design MRAC adaptive controllers for time-varying systems
Build fuzzy logic control systems without precise mathematical models
Model physical systems in Simscape without deriving equations
Go from continuous → discrete → C code, deploy to STM32 and other embedded platforms
Understand cascaded PI and FOC vector control in industrial practice

Project Structure

.
├── check_setup.m                 # Environment checker (run this first)
├── t00_main_guide.m              # Tutorial index
├── t01-t25_*.m                   # 25 tutorial scripts
├── models/                       # Simulink models (auto-generated)
│   └── tutorial01-tutorial25.slx
├── utils/                        # Shared utilities
│   └── getSimData.m
├── run_all_tutorials.m           # Batch runner for all tutorials
├── docs/images/                  # Auto-generated simulation figures
├── .github/                      # Issue/PR templates
├── README.md                     # 中文版
├── README_EN.md                  # This file (English)
├── CHANGELOG.md                  # Changelog
├── CONTRIBUTING.md               # Contribution guide
├── CODE_OF_CONDUCT.md            # Code of conduct
├── SECURITY.md                   # Security policy
└── LICENSE                       # MIT

Companion Projects

STM32-MPU6050-System — MEMS gyroscope Allan variance + adaptive Kalman on real hardware
ebpf-robot-safety — eBPF real-time control safety monitoring

Contributing

Issues and PRs are welcome! Bug reports, new tutorial ideas, and documentation improvements all count.

Bug → use Bug Report template
New topic → use Tutorial Request template
Code/doc improvements → Fork → Modify → PR

See CONTRIBUTING.md for details.

Star History

License

MIT — Free to use, modify, and distribute. See LICENSE.

If this tutorial helps you, a ⭐ Star would be greatly appreciated!

_{Xing Dong · 2026}

Navigation Menu

Simulink Control Engineering Tutorial

Table of Contents

Preview

Quick Start

Step 1: Clone

Step 2: Check your environment

Step 3: Start learning

Step 4: Follow the learning path

After each lesson

Prerequisites

FAQ

Tutorial Overview

Phase 1 — Simulink Fundamentals (t01-t08)

Phase 2 — Classical Control Design (t16, t17, t22)

Phase 3 — Modern Control Theory (t09-t12)

Phase 4 — Advanced Control Topics (t18-t21, t23, t24)

Phase 5 — Applications & Deployment (t13, t14, t25, t15)

Learning Path

What You'll Learn

Project Structure

Companion Projects

Contributing

Star History

License

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README_EN.md

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README_EN.md

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Simulink Control Engineering Tutorial

Table of Contents

Preview

Quick Start

Step 1: Clone

Step 2: Check your environment

Step 3: Start learning

Step 4: Follow the learning path

After each lesson

Prerequisites

FAQ

Tutorial Overview

Phase 1 — Simulink Fundamentals (t01-t08)

Phase 2 — Classical Control Design (t16, t17, t22)

Phase 3 — Modern Control Theory (t09-t12)

Phase 4 — Advanced Control Topics (t18-t21, t23, t24)

Phase 5 — Applications & Deployment (t13, t14, t25, t15)

Learning Path

What You'll Learn

Project Structure

Companion Projects

Contributing

Star History

License