Identification and Estimation

Code:

EEC0101

Acronym:

IEST

Keywords
Classification	Keyword
OFICIAL	Automation, Control & Manufacturing Syst.
OFICIAL	Basic Sciences for Electrotechnology

Instance: 2014/2015 - 1S

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

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIEEC	41	Syllabus	5	-	6	56	162

Teaching language

Portuguese

Objectives

1. Acquisition of  the theoretical basis for understanding the estimation and identification problems as well as the methods that today constitute the "state of the art" in this area.


2. To understand the state estimation problem and tpo know how to use the Kalman filter.


3. To understand identification problem with emphasis on linear systems knowing different approaches to the estimation of discrete-time parametric and nonparametric input/output models and state-space models.

Learning outcomes and competences

1. Understandinf the concept of state estimationKnowing how to implement and to use the Kalman filter.


2. Understanding Advanced Linear algebra concepts essential for  digital signal processing.


3. Understanding state-space representations of dynamical systems.


4. Knowing different input/output models.


5. Understanding and knowing how to implement some System Identification Algorithms.


6. At the end of this UC a student will be able to project and to implement a Kalman Filter. to plan and to performa a system identification experiment in ordewr to obtain a model to solve a given problem.

 

Working method

Presencial

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

• Control Theory


• Algebra


• Probabilities and Statistics

Program

Part I - State Estimation

• Deterministic Observers
• Introduction to stochastic processes
• Deterministic-Stochastic State-Space Models
• Kalman predictor and filter 

Part II - System Identification Theorectical tools

• Complements of Linear Algebra 
• State-Space analysis of Linear Time Invariant Systema
• Stochastic Processes
• Linear Prediction Theory
• Input/Output Stochastic Models
• Input/Output Deterministic-Stochastic Models

Part III - System Identification

• Least Squares Estimation
• Impulse Response Estimation
• Input/Output models identification
• Least Squares
• Instrumental Variables
• Deterministic Realization Theory
• Deriving state-space models from the Impulse Response

 

Mandatory literature

Katayama, Tohru; Susbspace Methods for System Identification, Springer-Verlag , 2005. ISBN: 1852339810
Lopes dos Santos, Paulo; Tópicos de Álgebra Linear, 2007
Lopes dos Santos, Paulo; Processos Estocásticos e Filtro de Kalman, 2007
Ljung, Lennart; System identification. ISBN: 0-13-881640-9
Lopes dos Santos, Paulo; Sistemas Lineares e Invariantes no Tempo ("Lecture Notes escritas para esta disciplina), 2007

Complementary Bibliography

Van Overschee, Peter; Subspace identification for linear systems. ISBN: 0-7923-9717-7
Delgado, Catarina Judite Morais; Identificação no subespaço de estados de sistemas lineares
Verhaegen, Michel and Verdult, Vincent; Filtering and System Identification - A least squares approach, Cambridge University Press, 2007. ISBN: ISBN-13 978-0-521-87512-7
Paulo Jorge de Azevedo Lopes dos Santos; Identificação de sistemas dinâmicos
Lopes dos Santos, Paulo; Perdicoúlis, T-P A; Novara, Carlo; Ramos, Jose; Rivera, Daniel; Linear Parameter Varying Systems - New Developments and Trends, World Scientific, 2012. ISBN: 13-978-981-4355-44-5

Teaching methods and learning activities

• Theoretical Lectures: Subject exposition using slides and the board. 


• TP Lectures: Execution of Lab works with real or simulated data to demonstrate of concepts. Small Identification and Estimation Projects.

Software

Matlab 6
System Identification Toolbox - Release 11
Interactive System Identification Tool

keywords

Technological sciences > Engineering > Systems engineering > Systems theory

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	50,00
Participação presencial	12,50
Trabalho laboratorial	37,50
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	84,00
Frequência das aulas	56,00
Trabalho laboratorial	28,00
Total:	168,00

Eligibility for exams

Do not exceed the absence limit.

Calculation formula of final grade

Final gradel=0.375*TL+0.125*Q+0.5*E

TL - Lab Works
Q - Quizzes
E - Examination

 An oral exame is required for those students who want more than 18

Special assessment (TE, DA, ...)

The students admitted to the examination because they were released from attending the lectures (according to points a) b) c) of Article 4 of the General Evaluation Rules), will make the ordinary witten examination. The Working students will only be graded by the final examination.

Classification improvement

The classification improvement can be made in special examination period . The examination grade will be the final grade if better than the previous one.

Observations

Students who obtained frequency in the previous year  (only in the previous year)  are loose this privelige if they register in a  TP class.