Modern control and state space representation

Name: Modern control and state space representation
Rating: 4.3 (8 reviews)

Dynamic systems modeling and controlling by state space representation

Created byHazem Ahmed

Last updated 6/2020

English

What you'll learn

State space representation
State feedback
Controllability and observability
Output feedback
Some concepts about eigenvalues and eigenvectors

Course content

4 sections • 15 lectures • 3h 15m total length

Introduction 19:44
Apply Newton's laws to model a mass-spring-damper system, derive equations of motion for single and two-mass configurations, and analyze linear two-degree-of-freedom dynamics with force inputs.
Tutorial 15:42
This tutorial presents a car-like model with two springs and a mass, showing linear and rotational motion as a two-degree-of-freedom system. It uses small-angle linearization and derives the equations of motion.
Introduction 25:27

State space concept18:19
Obtaining state space representation17:02
Tutorial 219:39
Explore deriving state-space representations from circuit differential equations, transforming them into matrix form for single and multi-input systems, with emphasis on state variables, inputs, and outputs.
CCF & OCF21:21
Tutorial 314:58
Convert a transfer function to a state-based representation using cross multiplication and time-domain derivatives, then build state equations and a block diagram in CCF.
Cascade and parallel realization12:43
Tutorial 45:29

Requirements

Classical control
Matrices
Differential equations and laplace transform

Description

This course is for students who completed their classical control course and want to take the next step, The course contains lectures in which the concept is explained and tutorials to solve problems based on the lectures. The course covers

1) modeling of mass spring system

2) transfer functions and laplace transform

3) state space representation

4) CCF & OCF

5) cascade and parallel realization

6) controllability and observability

7) state feedback

8) output feedback

As well as a recap on stability, eigenvalues and eigenvectors.

Who this course is for:

Mechatronics students
Control engineers

Modern control and state space representation

What you'll learn

Explore related topics

Course content

Introduction3 lectures • 21min

State space7 lectures • 1hr 50min

Controllability and observability1 lecture • 8min

State and output feedback4 lectures • 57min

Requirements

Description

Who this course is for: