Control Systems: From Mathematical Modelling to PID Control from Udemy

Today, control systems are everywhere: in cars, military aircrafts, interplanetary rockets, computers, fridges, washing machines, etc. As technology advances, control engineering allows us to design systems which make the most complicated machines do exactly what we want them to do with outstanding accuracy and reliabilty.

This course gives you the opportunity to understand, use and design the following:

- Mathematical Modelling of Engineering Systems.- Laplace Transforms and Linear Differential Equations.- Systems' Transfer Functions, Stability and Block Diagrams.- Open Loop Control, Closed Loop Control and Steady State Performance.- Proportional (P), Proportional Integral (PI), Proportional Derivative (PD), Proportional Derivative Feedback (PDFB) Controllers.- Proportional Integral Derivative (PID) Controller Design and Empirical Ziegler-Nichols Method.I will thoroughly detail and walk you through each of these concepts and techniques and explain down to their fundamental principles, all concepts and subject-specific vocabulary. This course is the ideal beginner, intermediate or advanced learning platform for control systems, the mathematics and the engineering behind them. Whatever your background, whether you are a student, an engineer, a sci-fi addict, an amateur roboticist, a drone builder, a computer scientist or a business or sports person, you will understand the brains behind our most advanced technologies.

If you have questions at any point of your progress along the course, do not hesitate to contact me, it will be my pleasure to answer you within 24 hours.

If this sounds like it might interest you, for your personal growth, career or academic endeavours, I strongly encourage you to join. You won't regret it.

What's inside

Learning objectives

Understand how systems and signals interact in engineering systems.
Model mechanical engineering systems mathematically.
Model electrical and electro-mechanical engineering systems mathematically.
Apply laplace transforms to engineering systems and easily solve differential equations.
Fully understand and manipulate transfer functions.
Fully understand stability in engineering systems.

Manipulate and use block diagrams for engineering systems and control design.
Understand and fully grasp control theory including open loop and closed loop control.
Design proportional (p), proportional integral (pi), proportional derivative (pd), proportional derivative feedback (pdfb) and proportional integral derivative (pid) controllers.
Use the empirical ziegler nichols method to design effective p, pi and pid controllers.
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Understand how systems and signals interact in engineering systems.
Model mechanical engineering systems mathematically.
Model electrical and electro-mechanical engineering systems mathematically.
Apply laplace transforms to engineering systems and easily solve differential equations.
Fully understand and manipulate transfer functions.
Fully understand stability in engineering systems.
Manipulate and use block diagrams for engineering systems and control design.
Understand and fully grasp control theory including open loop and closed loop control.
Design proportional (p), proportional integral (pi), proportional derivative (pd), proportional derivative feedback (pdfb) and proportional integral derivative (pid) controllers.
Use the empirical ziegler nichols method to design effective p, pi and pid controllers.
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Syllabus

Mathematical Modelling for Engineering Systems

Systems and Signals

Mechanical Systems

Electro-mechanical Systems

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Read about what's good

what should give you pause

and possible dealbreakers

Explores mathematical modeling, Laplace transforms, and transfer functions, which are fundamental concepts in control systems engineering

Covers PID controller design and the Ziegler-Nichols method, which are essential for practical control system implementation

Details block diagrams and stability analysis, which are crucial for understanding system behavior and performance

Examines open-loop and closed-loop control, which are core concepts in feedback control systems

Includes a discount for a course using MATLAB/Simulink, which may require learners to purchase additional software

Focuses on continuous-time controller design, which may not cover modern discrete-time control methods used in digital systems

Reviews summary

Foundational control systems theory

According to learners, this course provides a solid theoretical foundation in control systems, with the instructor offering remarkably clear explanations for complex topics like Laplace transforms, transfer functions, and PID controllers. Students highlight that it covers core topics thoroughly. However, it has a strong theoretical focus and lacks practical software implementation (like MATLAB). Prospective students should be aware that the course requires a good grasp of calculus and differential equations.

Pace is manageable but might require re-watching.

"I felt the pace was good, although some parts required re-watching."

"sometimes felt a bit dry."

"the pace felt too fast through complex mathematical steps."

Provides deep understanding of core principles.

"It provides a solid theoretical foundation for control systems, covering P, PI, and PID controllers thoroughly."

"It's theoretical, which is fine, but don't expect much software implementation (like MATLAB)."

"This course provides a strong conceptual understanding. It is indeed theory-focused, which is appropriate for a foundational course..."

"It's definitely geared towards theory and requires mathematical maturity."

"Prepare for a lot of math. The explanations are decent, but sometimes felt a bit dry."

"As an engineering student, this really solidified my understanding of control systems theory."

"It's a solid theoretical primer."

Instructor clarifies complex topics well.

"The instructor explains complex concepts like Laplace transforms and transfer functions with remarkable clarity. I finally understood these topics."

"Fantastically clear explanations. The instructor takes time to break down difficult topics step-by-step."

"The lectures were clear for the most part."

"While the instructor tries to be clear, the pace felt too fast through complex mathematical steps."

Key control systems concepts explained well.

"The instructor explains complex concepts like Laplace transforms and transfer functions with remarkable clarity."

"The coverage of PID control design using Ziegler-Nichols is a strong point."

"The sections on stability and block diagrams were particularly helpful."

"The sections on transfer functions and open/closed loop control were well-explained."

"Amazing course on control theory fundamentals. The explanation of transfer functions, poles, zeros, and stability was top-notch."

Requires prior knowledge in calculus/diff eq.

"The course is quite dense and requires a good grasp of calculus and differential equations beforehand."

"It's definitely geared towards theory and requires mathematical maturity."

"Prepare for a lot of math."

"The mathematical prerequisites were higher than I expected, making it difficult to follow the derivations."

Course is light on software implementation.

"While it's theory-heavy... don't expect much software implementation (like MATLAB)."

"learners interested in immediate practical application might need a follow-up course."

"Could benefit from some simple practical examples or suggested tools for implementation."

"Not much in the way of practical application or visual intuition, which I needed."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Control Systems: From Mathematical Modelling to PID Control with these activities:

Review Laplace Transforms

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Refresh your understanding of Laplace Transforms to better grasp their application in solving differential equations within control systems.

Browse courses on Laplace Transforms

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Review the definition and properties of Laplace Transforms.
Practice solving differential equations using Laplace Transforms.
Work through examples of applying Laplace Transforms to mechanical and electrical systems.

Read 'Modern Control Systems' by Richard Dorf and Robert Bishop

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Expand your knowledge of control systems with a comprehensive textbook that covers both theoretical foundations and practical applications.

View Modern Control Systems (Fourteenth Edition,... on Amazon

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Read the chapters related to mathematical modeling and transfer functions.
Work through the example problems and exercises in the book.
Compare the book's approach to controller design with the methods taught in the course.

Simulate Control Systems in MATLAB/Simulink

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Reinforce your understanding of control systems by simulating various systems and controllers using MATLAB/Simulink.

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Model a simple mechanical system in Simulink.
Design a PID controller for the system and simulate its performance.
Experiment with different controller parameters to optimize performance.

Three other activities

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Design a Control System for a DC Motor

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Apply your knowledge to a practical project by designing a control system for a DC motor, a common component in many engineering applications.

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Model the DC motor mathematically.
Design a PID controller to regulate the motor's speed or position.
Simulate the control system in MATLAB/Simulink.
Implement the control system on a physical DC motor (optional).

Read 'Control Systems Engineering' by Norman S. Nise

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Supplement your learning with another widely-used textbook that offers a different perspective on control systems concepts and design techniques.

View Control Systems Engineering, International... on Amazon

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Read the chapters on PID controller design and tuning.
Compare Nise's approach to Ziegler-Nichols tuning with the course material.
Work through the case studies to see how control systems are applied in real-world scenarios.

Create a Blog Post on PID Controller Tuning Methods

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Solidify your understanding of PID controller tuning by writing a blog post explaining different methods, including the Ziegler-Nichols method.

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Research different PID controller tuning methods.
Write a clear and concise explanation of each method.
Include examples and diagrams to illustrate the concepts.
Publish the blog post online.

Career center

Learners who complete Control Systems: From Mathematical Modelling to PID Control will develop knowledge and skills that may be useful to these careers:

Control Systems Engineer

As a Control Systems Engineer, your work involves designing, developing, and testing control systems. This course directly aligns with the core responsibilities of a Control Systems Engineer. The course helps build a foundation in mathematical modeling of engineering systems, understanding transfer functions, and designing various controllers like Proportional Integral Derivative. You will gain proficiency in crucial areas such as stability analysis and block diagram manipulation. Taking this course ensures you are well-versed in the fundamental principles and techniques essential for succeeding as a Control Systems Engineer. The knowledge presented in the course may be especially useful.

See salaries and explore the career path for Control Systems Engineer

Robotics Engineer

The Robotics Engineer designs, builds, and programs robots for various applications. This course provides a strong foundation for understanding the control systems that govern robotic movement and behavior. The course helps build a foundation in mathematical modeling, Laplace transforms, and the design of controllers such as Proportional Integral Derivative, all of which are crucial for developing sophisticated robotic systems. You will understand both open and closed loop control. This course may be especially helpful to you as a Robotics Engineer.

See salaries and explore the career path for Robotics Engineer

Mechatronics Engineer

A Mechatronics Engineer integrates mechanical, electrical, and computer engineering principles to design automated systems. This course directly addresses the core competencies required for this role. Your work involves designing and implementing control strategies for complex mechatronic systems and the course allows you to understand stability in engineering systems. The course helps build a foundation in mathematical modeling of electromechanical systems and Laplace transforms. The course may be especially useful.

See salaries and explore the career path for Mechatronics Engineer

Automation Engineer

The Automation Engineer designs and implements automated processes and systems, often in manufacturing or industrial settings. This course provides a deep dive into control theory and design, which is essential for making an impact and succeeding in this role. The course helps build a foundation in understanding transfer functions, designing Proportional Integral Derivative controllers, and using methods like the Empirical Ziegler Nichols Method. You will understand how systems and signals interact in engineering systems. The course may be especially useful.

See salaries and explore the career path for Automation Engineer

Aerospace Engineer

Aerospace Engineers design aircraft, spacecraft, and related systems, all of which rely heavily on control systems. This course gives you access to the foundations required to design and analyze aerospace control systems. The course helps build a foundation in mathematical modeling, Laplace transforms, and stability analysis. You will understand both open and closed loop control. The course may be especially helpful.

See salaries and explore the career path for Aerospace Engineer

Process Control Engineer

The Process Control Engineer implements and maintains control systems in manufacturing or chemical processing plants. This course will provide the knowledge and understanding of Proportional Integral Derivative controllers that are often at the heart of process control strategies. The course helps build a foundation in block diagram manipulation and controller design. You will understand how systems and signals interact in engineering systems. This course may be especially useful.

See salaries and explore the career path for Process Control Engineer

Systems Analyst

Systems Analysts evaluate and improve existing computer systems. Though this role is not strictly engineering, a course in control systems may be helpful. As a Systems Analyst, you may be asked to create system diagrams. Therefore, the information about block diagrams may be useful. The course may be helpful toward understanding systems design and control.

See salaries and explore the career path for Systems Analyst

Electrical Engineer

Electrical Engineers design, develop, and test electrical equipment and systems. This course may be useful for Electrical Engineers who specialize in control systems or automation. You will learn about mathematical modeling of electromechanical systems and the use of Laplace transforms which will further improve the quality of your work as an Electrical Engineer. The course may be especially useful.

See salaries and explore the career path for Electrical Engineer

Mechanical Engineer

Mechanical Engineers design and oversee the manufacturing of many different machines. Often machines require control systems to be operated and maintained. This course will help you understand how control systems are designed. The course helps build a foundation in mathematical modeling of mechanical systems. The course may be especially helpful.

See salaries and explore the career path for Mechanical Engineer

Instrumentation Engineer

Instrumentation Engineers design and install instruments and control systems to monitor and control industrial processes. This course may be useful to help give an overview of control systems. The course helps build a foundation in understanding control theory. It can also help you learn how to manipulate and use block diagrams for engineering systems and control design. The course may be helpful.

See salaries and explore the career path for Instrumentation Engineer

Firmware Engineer

Firmware Engineers design, develop, and test low-level software that controls hardware devices. This course may be useful for Firmware Engineers who work with embedded systems requiring precise control. You will understand how systems and signals interact in engineering systems. The course helps build a foundation in understanding and designing Proportional Integral Derivative controllers. The course may be helpful.

See salaries and explore the career path for Firmware Engineer

Automotive Engineer

Automotive Engineers design and develop vehicles and their systems, including control systems for engine management, braking, and stability control. This course may be useful for understanding the principles behind these control systems. The course helps build a foundation in mathematical modeling of engineering systems and the design of Proportional Integral Derivative controllers. You will understand both open and closed loop control. The course may be helpful.

See salaries and explore the career path for Automotive Engineer

Software Engineer

Software Engineers may find this course helpful if they work on projects involving control systems or simulations. This course may be useful to understand systems design. The course helps build a foundation in understanding how systems and signals interact in engineering systems. You will understand both open and closed loop control. The course may be helpful.

See salaries and explore the career path for Software Engineer

Manufacturing Engineer

Manufacturing Engineers improve manufacturing processes and systems, which often involves control systems for automated machinery. This course may be useful to understand the principles behind these control systems and how to optimize them. The course helps build a foundation in understanding control theory and designing Proportional Integral Derivative controllers. The course may be helpful.

See salaries and explore the career path for Manufacturing Engineer

Data Scientist

Data Scientists analyze complex data sets to extract insights and inform decision-making. While seemingly unrelated, this course may be useful for Data Scientists working in fields where understanding dynamic systems is important. The course helps build a foundation in mathematical modeling and system analysis. You will understand how systems and signals interact in engineering systems, and how best to control these signals. The course may be helpful.

See salaries and explore the career path for Data Scientist

Control Systems

From Mathematical Modelling to PID Control

What's inside

Learning objectives

Syllabus

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Reviews summary

Foundational control systems theory

Activities

Career center

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