Control and Systems

Code:

M.EEC003

Acronym:

SCO

Keywords
Classification	Keyword
OFICIAL	Automation and Control

Instance: 2024/2025 - 1S

Active?	Yes
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Master in Electrical and Computer Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M.EEC	94	Syllabus	1	-	6	39	162

Teaching language

English

Objectives

Analysis and design of linear dynamic control systems in both contexts of continuous time and sampled data.
Proficiency in the use of computational tools to suport the analysis and design of controllers for dynamic linear systems.

Learning outcomes and competences

At the end of the course the students should be able to:

1. Model and analyze linear dynamic control systems by using methods and tools in the frequency domain and in the time domain.
2. Analyze linear dynamic control systems represented in the state space and design linear feedback controllers and linear state estimators in both discrete and continuous time.
3. Formulate linear quadratic optimal control problems and compute their optimal control strategies.
4. Use computacional tools to support the analysis of control systems and the design of controllers.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Linear Algebra, Calculus, Signal and Systems.

Program

State Space (Systems in continuous and discrete time domains).

Brief review of pertinent topics in Algebra (eigenvectors, eigenvalues, coordinates change).
The concept of state.
State space modeling: Differential equations of order n and the (A,B,C,D) representation.
Canonical forms: controllable, observable, and diagonal.
Time response: Variation of parameters formula.
Methods to compute the exponential of a matrix.
Poles localization and time response.
Controllability. Observability.
Pole placement: Linear state feedback controller. State estimator by output error linear feedback.
Independence of the designs of the linear controller and estimator.
Linear state estimate feedback controller
Introduction to stability in the state space domain.
Linear quadratic regulator.

Mandatory literature

Ogata, Katsuhiko; Modern Control Engineering. ISBN: 0-13-598731-8

Complementary Bibliography

Ogata, Katsuhiko; Discrete-time control systems. ISBN: 0-13-216227-X
Carvalho, Jorge Leite Martins de; Sistemas de controle automático. ISBN: 85-216-1210-9
João Miranda Lemos; Controlo no Espaço de Estados.. ISBN: ISBN: 978-989-8481-70-2

Teaching methods and learning activities

Exposition lectures: Presentation and discussion of the various topics of the curricular unit. Detailed explanation of examples of application of concepts and methods.
Exercises solving classes: Practical exercises are solved by the students with the support of the teacher by clarifying the issues that they might raise. Follow-up of the work in the mini projects support by the use of MATLAB.

Software

Matlab
Octave
Python

keywords

Technological sciences > Engineering > Systems engineering > Systems theory
Physical sciences > Mathematics > Applied mathematics
Technological sciences > Engineering > Electrical engineering
Technological sciences > Engineering > Control engineering > Automation

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	70,00
Trabalho prático ou de projeto	30,00
Trabalho escrito	0,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de projeto	20,00
Estudo autónomo	110,00
Frequência das aulas	63,00
Total:	193,00

Eligibility for exams

Frequency status is obtained through participation in at 
least 75% of the TP classes and through participation in 
the mini-project. 

Calculation formula of final grade

The final evaluation has two components:

EF - Valuation of the Final Exam on a scale of 0 to 
20  ​​with a weight of 70%

CC - Valuation of the Continuous Component on a scale 
of 0 to 20  ​​with a weight of up to 30%



Final Classification = 0.7 EF + 0.3 CC



The Continuous Component is assessed by the performance 
in the group project and the degree of participation of 
the PL Lesson 

Project performance will be valued up to 6 points (30%), but 
not exceding in more than 4 points the classification of the exam.

CC= min{E+4,P}

In case of Conducting the resit exam ("exame de recurso"), that is valued up to 20, 
the total final classification.

Examinations or Special Assignments

Mini-project: design a control system using MATLAB or Python.

Internship work/project

NA

Special assessment (TE, DA, ...)

Similar to the resit exam, valued up to 20, the total final classification.

Classification improvement

Conducting the resit exam ("exame de recurso"), that is valued up to 20, 
the total final classification.