Materiale didattico/ Course material

 

Material for the course “Fault Diagnosis and Estimation in Dynamical Systems” (a.a. 2019/2020):

Part of the study material of FDE consists in the slides presented during the lectures and the Matlab scripts developed during both the lectures and the exercitations:

Lecture 2

Lecture 3

Lecture 4

Lecture 5

Lecture 6

Lecture 7 – Matlab scripts

Lecture 8

Lecture 9

Lecture 10

Lecture 11

Lecture 12

Lecture 12 – Matlab scripts

Lecture 13

Lecture 13 – Matlab Simulink and script

Lecture 14

Lecture 15

Lecture 15 – Matlab Simulink and script

Lecture 16

Lecture 17 

Lecture 17 – Matlab script

Lecture 18

Lecture 18 – Matlab Simulink file

Lecture 18 part II

Lecture 19

Lecture 20

Lecture 21

Lecture 21 – Matlab scripts

Suggested books and other material:

Material on continuous time linear systems, stability, observability and controllability, Lyapunov methods, state feedback, and  state observers in Italian, is found in:
  • Alessandro GIUA, Carla SEATZU, Analisi dei sistemi dinamici- 2a edizione, Springer-Verlag Italia, Milano, 2009.  (Chapter 4, 8, 11)
Material on discrete-time and continuous time linear systems, stability, observability and controllability, state feedback,  Lyapunov methods Luenberger observers,  is found in:
  • Katsuhiko Ogata, “Discrete-time control systems” second edition, Prentice Hall International editions, 1995  (Part of chapter 1, 5, 6)
Material on Fault diagnosis and Estimation is found in:
  • Silvio Simani, Cesare Fantuzzi and Ron J. Patton “Model-based fault diagnosis in dynamic systems using identification techniques” Springer-Verlag 2002. (Part of chapters 1,2,3,4)

Material on high gain observers (and Lyapunov methods) is found in:

  • Hassan K. Khalil “Nonlinear systems” third edition, Pearson Eduction Limited 2014.  (Part of chapter 14)

Additional material on nonlinear analysis, Lyapunov methods  is found in

  • Jean-Jacques E. Slotine, Weiping Li “Applied Nonlinear Control” Prentice-Hall, 1991.  (Part of chapter 3)

Suggested readings:

Tutorial on Kalman filters:

  • Matthew B. Rhudy, Roger A. Salguero and Keaton Holapp, “A Kalman filtering tutorial for undergraduate students” International Journal of Computer Science & Engineering Survey (IJCSES) Vol.8, No.1, February 2017.

Tutorials on High-Gain Observers:

  • Ahmed Mohammed Dabroom and Hassan K. Khalil, “Output Feedback Sampled-Data Control of Nonlinear Systems Using High-Gain Observers” IEEE TRANSACTIONS ON AUTOMATIC CONTROL, VOL. 46, NO. 11, NOVEMBER 2001
  • Hassan K. Khalil “High-Gain Observers in Nonlinear Feedback Control” International Conference on Control, Automation and Systems 2008, Oct. 14-17, 2008 in COEX, Seoul, Korea

Other sources and papers will be provided during the lectures.

Students can download an academic version of the Matlab software by following the instructions (in Italian) at: https://www.unica.it/unica/en/studenti_s08_ss09.page

 

During the lectures, a total of six assignments with questions and exercises will be provided.

The final exam is oral and the students will be expected to understand, solve and discuss the provided assignments.

The final evaluation will be quantified by a mark representing a weighted average in the next areas:

  • Knowledge of the topics (40% final mark)
  • Application of the obtained knowledge to the design algorithms (30% final mark)
  • Autonomy in making judgments in regard to design choices (20% final mark)
  • Use of technical language (10% final mark)

Examples of typical exam questions can be found here

Vedemecum and where to study for a.a. 2019/2020

Course assignments a.a. 2018/2019

Assignment 1

Assignment 2

Assignment 3

Assignment 4

Assignment 5

Assignment 6

Assorted Matlab scripts discussed during the lectures can be found here:

AssortedMatlabScripts

Short summary of course content  (a.a. 2018/2019)

Representation of dynamical systems:

State space representation of continuous time and discrete time dynamical systems. Analysis of continuous time linear systems, natural and forced response.  Analysis of discrete-time linear systems, natural and forced response. Discretization of dynamical systems.  Canonical forms of linear systems, continuous time and discrete time.

Where to study:

  • Lecture notes;
  • Katsuhiko Ogata, “Discrete-time control systems” Chapter 5, Sections 5.1,5.2,5.3,5.5.

Stability of dynamical systems:

Equilibrium points. Stability and Asymptotic stability of equilibrium points. Stability criteria for continuous time and discrete-time linear systems. Linearization of a nonlinear system around an equilibrium point. Stability of nonlinear systems: indirect (also called first) and direct (also called second) Lyapunov methods for  continuous time and discrete time dynamical systems.

Where to study:

  • Katsuhiko Ogata, “Discrete-time control systems” Chapter 5, Section 5.6.

Structural properties of dynamical systems and state feedback:

Controllability and Observability.  Controllable and observable canonical forms. Controllability and observability matrix. Full-state  feedback control by eigenvalue assignment. Design procedure.

Where to study:

  • Katsuhiko Ogata, “Discrete-time control systems” Chapter 6, sections 6.1,6.2,6.3,6.4,6.5.

Estimation in dynamical systems:

The state estimation problem, asymptotic (Luenberger) state observers. Full-order and reduced (minimum) order observers. Design procedure. Observer-state feedback and Separation principle. Kalman filter (Discrete-time) and Extended Kalman filters. Nonlinear systems and High-gain observers.

Where to study:

  • Katsuhiko Ogata, “Discrete-time control systems” Chapter 6, section 6.6;
  • Matthew B. Rhudy, Roger A. Salguero and Keaton Holapp, “A Kalman filtering tutorial for undergraduate students” International Journal of Computer Science & Engineering Survey (IJCSES) Vol.8, No.1, February 2017;
  • Hassan K. Khalil “Nonlinear systems” third edition, Pearson Eduction Limited 2014.  Chapter 14, section 14.5, 14.5.1, 14.5.2.

Fault diagnosis:

Introduction to Fault Detection and Identification (FDI). Methods for model based  fault diagnosis. Fault models.  The residual generation and evaluation problem. Unknown input observers. FDI by banks of unknown input observers. Parameter estimation for discrete-time linear systems. Residual generation by parameter estimation methods.

Where to study:

  • Silvio Simani, Cesare Fantuzzi and Ron J. Patton “Model-based fault diagnosis in dynamic systems using identification techniques” Springer-Verlag 2002.  Chapter 1, Sections 1.1, 1.2,1.3,1.4,1.5. Chapter 3, Sections 3.1,3.2,3.3.1. Chapter 4, Sections 4.1,4.2,4.3,4.4, 4.8.

 

 

 


 

Material for the course “Control of Network Systems”

The adopted textbook for the course “Control of Network Systems” is:

Francesco Bullo “Lectures on Network Systems“, draft version 0.95(b), 2017

The textbook is available online at:  http://motion.me.ucsb.edu/book-lns/

Further material consisting in scientific papers and matlab scripts is  handed out during the lectures and is available upon request.

Other suggested readings:

M. Mesbahi and M. Egerstedt. “Graph Theoretic Methods for Multiagent Networks“, Princeton University Press, Princeton, NJ, Sept. 2010.

Ishii, Hideaki, and Roberto Tempo. “The PageRank problem, multiagent consensus, and web aggregation: A systems and control viewpoint.” IEEE Control Systems 34.3 (2014): 34-53.

Course assignments (a.a. 2017/2018):

Assignment 1

Assignment 2

Assignment 3

Assignment 4

Assignment 5

Assignment 6

 

Course assignments (a.a. 2016/2017):

Assignment 1 

Assignment 2

Assignment 3

Assignment 4

Assignment 5

Assignment 6

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