Applied Control Systems 1: autonomous cars: Math + PID + MPC

Modeling + state space systems + PID + Model Predictive Control + Python simulation: lateral control for autonomous cars

4.55 (1363 reviews)

Udemy

platform

English

language

Engineering

What you will learn

mathematical modelling of systems

reformulating models into state-space equations

applying a PID controller to systems (simple magnetic train catching objects)

applying Model Predictive Control (MPC) to systems (autonomous car: lane changing maneuvers)

Why take this course?

The world is changing! The technology is changing! The advent of automation in our societies is spreading faster than anyone could have anticipated. At the forefront of our technological progress is autonomy in systems. Self driving cars and other autonomous vehicles are likely to be part of our every day lives. How would you like to understand and be able design these autonomous vehicles? How would you like to understand Mathematics behind it?

Welcome! In this course, you will be exposed to one of the most POWERFUL techniques there are, that are able to guide and control systems precisely and reliably.

You are going to DESIGN, MASTER and APPLY:

mathematical models in the form of state-space systems and equations of motion
a PID controller to a simple magnetic train that needs to catch objects that randomly fall from the sky
a Model Predictive Controller (MPC) to an autonomous car in a simple lane changing maneuver on a straight road at a constant forward speed.

You will LEARN the fundamentals and the logic of Modelling, PID and MPC that will allow you to apply it to other systems you might encounter in the future.

You need 3 things when solving an Engineering problem: INTUITION, MATHEMATICS, CODING! You can't choose - you really need them all. After this course, you will master Modelling, PID and MPC in all these 3 ways. That's a promise!

I'm very excited to have you in my course and I can't wait to teach you what I know.

Let's get started!

Screenshots

Applied Control Systems 1: autonomous cars: Math + PID + MPC - Screenshot_01

Applied Control Systems 1: autonomous cars: Math + PID + MPC - Screenshot_02

Applied Control Systems 1: autonomous cars: Math + PID + MPC - Screenshot_03

Applied Control Systems 1: autonomous cars: Math + PID + MPC - Screenshot_04

Reviews

Ihor

November 5, 2023

Good course overall. Mathematical derivations are very long and tedious, but its possible to get the idea nevertheless. Although one has to go through the math to actually understand MPC

Pablo

October 14, 2023

Having a degree in Aerospace Engineering with aspirations of becoming a flight control engineer, this course has done wonders in helping me understand control theory. Furthermore, the in-depth mathematical approach has made everything click in my brain seamlessly. Well done prof!

Gal

September 20, 2023

The course covers the basic - It aims for clueless audience that just getting started with control theory

Nguyenhv

September 15, 2023

I was hesitant at first because the material seemed to be over my head (autonomous cars and drones), but I really enjoyed the course overview and it put my mind at ease. I look forward to going through the whole course to review basics and further improve my controls proficiency.

Robert

September 3, 2023

This course is absolute quality. This is taking many elements of my undergraduate and putting them all together. I'm half way through this course and bought the other two courses. This is the most extensive control systems course on the internet and the price is a bargain.

Kholood

August 7, 2023

As a student with a background in computer science, I was eager to expand my knowledge base into vehicle dynamics and control. This course precisely met my expectations! Prior to this, I took another course on vehicle dynamics from a different instructor, which served as an excellent precursor to this one on vehicle control. The video content was impeccably clear, and the pace of the lectures was suitable enabling an effective learning experience. However, I did encounter some complexities navigating through certain mathematical details, particularly those pertaining to the cost function formulation. In anticipation of future courses, I would sincerely appreciate it if the instructor could accommodate tutorials or course materials for MATLAB/Simulink users. This inclusion would certainly enrich the learning experience, especially for individuals like myself who are interested in practically applying the theoretical concepts presented in this course.

Adrian

July 21, 2023

The course gives a great overview and introduction about Control Theory including PID controllers and MPC controllers. The combination of deeply explaining the physical models together with the maths behind it creates a great understanding of the course content. Only critic from my side is, that sometimes the explanations are quit repetitive, i.e. the same explanations are repeated over and over. Thus the course in my opinion is longer than it needs to be.

Karimu

July 13, 2023

Not just a good match rather an eye opener to me. it very informative and equipping as everything is been unraveled step by step

Borja

July 7, 2023

The explanations starts from scratch and is phenomenal for someone who is new in controls or for someone who needs a quick update for all the knowledge that had acquired in the past.

June 28, 2023

This course is just awesome with the explanations and engaging simulation designing I will be very happy if you do any robotics courses with the same amount of theory-to-project ratio

Arvand

June 20, 2023

Great explanation and I loved the depth of the math, it was good enough for me to get a solid grip on the subject.

Twinkle

March 14, 2023

Amazing Course ! will be buying rest 2 of the series! looking forward to next control series course and any robotics related course or perhaps you can suggest any

Daniel

February 27, 2023

In general very good information. Sometimes it is a bit hard to follow due to the amount of information put on one slide/screen/page. Especially in Section 4 were the substitution took place for me it was easier when I wrote it down with the x_1, x_2 etc being on the left side for both cases. ----- Section 6 is very very hard to follow. I got lost in the various substitutions and getting back on track is almost impossible with the videos being named "Math 1 to x". It think that following things would help a lot: 1) Naming the videos based on what is done like "Derivation of the costfunction" "Costfunction to Costfunction of agumented system" 2) List all the substitution separately at the end of a derivation on a blank new slide to summarise.

Faisal

January 29, 2023

The training is amazing. if only it could start explaining the PID in general then go in to the examples

Erik

January 4, 2023

I appreciate the great amount of detail and careful explanation. At this point, I already know most of what's being covered (because it's very early in the course) but I am looking forward to having this same level of careful detail in the parts that are new to me.

Charts

Price

Rating

Enrollment distribution

Applied Control Systems 1: autonomous cars: Math + PID + MPC - Distribution chart