Complements of Control Systems

Code:

M.EM043

Acronym:

CSC

Keywords
Classification	Keyword
OFICIAL	Automation

Instance: 2023/2024 - 2S

Active?	Yes
Responsible unit:	Automation, Instrumentation and Control Section
Course/CS Responsible:	Master in Mechanical Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M.EM	31	Syllabus	1	-	6	39	162

Teaching language

English

Objectives

BACKGROUND: Mechanical Engineering evolution in the last decades has been strongly influenced by developments in the areas of Material Science, Computer Science, Automation and Control Systems. These have provided the means to produce systems with increased capabilities and functionality. This complexity increment has been matched by a need to take into account their nonlinear nature and behaviour that must be match by more sophisticated controllers. There are numerous cases with relevant social impact: transport means, burning systems, HVAC systems, robotic systems, commodity products, all with increased performances and energy efficiencies. .

Learning outcomes and competences

SPECIFIC AIMS: The present subject is compulsory only for students of the mechanical engineering degree that want to focus on the area of automation and control systems. So, it aims to endow these students with nuclear and structuring knowledge on nonlinear dynamic systems, modern automatic control, robust control and the basics of system identification. This will give them the capabilities to analyse, design and implement computer controlled nonlinear systems, use Computer-Aided Control System Design tools, both in system simulation and controller design, and identify system models using the least squares principle.

PERCENTUAL DISTRIBUTION: Scientific component (establishes and develops scientific bases) – 70% Technological component (apply to design and process operation) – 30% LEARNING OUTCOMES At the end of this subject students shall be able to: i) write lumped parameter models of nonlinear dynamic systems from manufacturer provided and other design data (Knowledge and Understanding; Engineering Analysis; Investigations); ii) carry out the time response of nonlinear dynamic systems (Engineering Analysis); iii) design continuous and discrete time modern controllers that enable the achievement of performance specifications (Engineering Design); iv) design time domain robust controllers for uncertain nonlinear systems (Engineering Design); v) use Computer-Aided Control System Design tools on the simulation and design of control systems (Engineering Design; Investigations; Engineering Practice; Transferable Skills) vi) identify time domain system models using the least squares principle (Knowledge and Understanding; Engineering Practice, Transferable Skills).

Working method

Presencial

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

PREVIOUS KNOWLEDGE EM0005: Vector Algebra; Matrices; Determinants; Systems of Linear Equations; Linear Spaces, Transformations and Matrices; Eigenvalues and Eigenvectors. EM0015: Systems of differential equations; Fourier Analysis. EM0016: Numerical integration: Newton-Cotes formulae; ODEs: Euler’s and Runge-Kutta methods; Adjusting functions in the least squares sense; Matlab language. EM0031: A/D and D/A conversion; Programming and using PLCs. EM0036: Measuring chains and systems; Measurement of physical quantities - transducers/sensors. EM0041: All

Program

1 Introduction to Discrete Time Control Systems
1.1 Structure of a discrete time control system.
1.2 Signal sampling: spectrum of a sampled signal; signal reconstruction; sampling frequency selection.
1.3 Implementation of PID controllers using finite-differences approximations.
1.4 Z transform: z transform of a sampled signal; transfer function of a sampled system; mapping between s and z spaces; sampled system stability.
1.5 Discrete time controller design: discrete approximation of a continuous controller using the bilinear or Tustin transform; controller design in the pseudo-frequency domain using the bilinear or Tustin transformation.

2 State-Space Theory.
2.1 State-Space representation of dynamic systems;
2.2 Invariance of the eigenvalues under a linear transformation of the state vector;
2.3 Solution of the state equation;
2.4 Diagonalization of the state matrix;
2.5 Controllability and Observability of a dynamic system.

3 Modern Control.
3.1 System stabilization, with pole placement, by state feedback;
3.2 The tracking problem;
3.3 Dynamic system state observer design;
3.4 Time sampling of continuous-time state-space system;
3.5 Discrete-time state feedback controllers and observers.

4 Nonlinear Systems Modelling and Analysis.
4.1 Some nonlinear systems behaviour phenomena;
4.2 The phase plane as a graphical tool for the analysis of second order systems;
4.3 Limit Cycles;
4.4 Time-domain Stability: Lyapunov theory.

5. Time-domain robust control.
5.1 Variable structure systems;
5.2 Sliding mode controllers;
5.3 Direct implementation of switching control laws;
5.4 Continuous approximations of switching control laws.

6 Introduction to System Identification.
6.1 System identification principles;
6.2 The principle of Least Squares;
6.3 Batch estimation using the Penrose pseudo-inverse matrix;
6.4 Recursive estimation.

Mandatory literature

Astrõm, Karl Johan; Computer Controlled Systems. ISBN: 0-13-164302-9
Katsuhiko Ogata; Modern Control Engineering, Pearson, 2010. ISBN: 978-0-13-615673-4 (5th edition)
Slotine, Jean-Jacques E.; Applied nonlinear control. ISBN: 0-13-040890-5

Complementary Bibliography

Van de Vegte, John; Feedback control systems. ISBN: 0-13-016379-1
Gene F Franklin; Digital control of dynamic systems. ISBN: 0-201-33153-5
Karl Johan Astrom and Richard M. Murray; Feedback systems : an introduction for scientists and engineers, Princeton University Press, 2008. ISBN: 978-0-691-13576-2 (Version 2.10c (4 Mar 2010): third printing)
Constantine H. Houpis, Stuart N. Sheldon; Linear Control System Analysis and Design with MATLAB, CRC Press, 2013. ISBN: 9781466504264 (6th edition)
Jinkun Liu; Advanced sliding mode control for mechanical systems. ISBN: 978-3-642-20907-9

Teaching methods and learning activities

Two types of lectures are used for:
- subject presentation illustrated by its application to some problem solving exercises;
- experimental demonstration of some automatic control systems and of the use of Computer-Aided Control System Design tools.

Software

Matlab / Simulink

keywords

Technological sciences > Engineering > Control engineering

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	70,00
Trabalho escrito	30,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de relatório/dissertação/tese	26,00
Estudo autónomo	90,50
Frequência das aulas	45,50
Total:	162,00

Eligibility for exams

To respect the absence limit and to obtain a minimum grade of 8.0 on a report paper about a modelling and computer simulation work using Matlab/Simulink.

Calculation formula of final grade

Report Classification: RC;
Exam Classification: EC;
Final Classification: FC;
FC = 0,3 RC + 0,7 EC.

Examinations or Special Assignments

A Written Report of a group work on control and computer simulation using Matlab/Simulink. Each group shall be composed by 2 students.

Special assessment (TE, DA, ...)

The student must do the final exam and produce a report about a work identical to the one required to ordinary students.

Classification improvement

The student may chose between improving the RC, by doing a new report, the EC, by doing a new exam, or both, by doing a new report and a new exam.