FI:IV120 Continuous and Hybrid Systems - Course Information
IV120 Continuous and Hybrid SystemsFaculty of Informatics
- Extent and Intensity
- 2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
- RNDr. David Šafránek, Ph.D. (lecturer)
prof. RNDr. Jiří Barnat, Ph.D. (lecturer)
- Guaranteed by
- RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing - Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing - Faculty of Informatics
- Timetable of Seminar Groups
- IV120/01: Thu 10:00–12:50 A418, D. Šafránek
- Elementary mathematical knowledge: linear algebra (matrix, linear map, eigenspace), calculus (continuous function, multi-variable diferential calculus, first-order differential equations).
Elementary knowledge of computer science: finite automata, state-transition system, behavioral equivalence, bisimulation.
General knowledge of modeling and simulation: population model, feedback, simulation.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- Fields of study the course is directly associated with
- there are 38 fields of study the course is directly associated with, display
- Course objectives
- Introduction to continuous and hybrid systems that are used to model many natural phenomena.
- Learning outcomes
- At the end of the course students should be able to:
understand elementary notions from the domain of continuous and hybrid systems;
orient themselves in methods for analysis of continuous and hybrid systems, system control and related problems;
characterize complexity of the given system;
apply computational methods to analyze dynamic properties of systems.
- Introduction to general systems theory. System, object, model. Boulding's hierarchy. Dynamical system, causality, state transition function. Dimensionality, state equations. Feedbacks, block diagram.
- Continuous, discrete, hybrid system. Trajectories, their existence, simulation. Examples of systems (electronics, economy, chemistry, biology).
- System presentation - system matrix and its meaning. Non-linear systems, classes of non-linearity, linearization. Stability, characterization of stability, Lyapunov theorems. Attractors and domains of attraction. Oscillation, multi-stability, chaos. Feinberg's classification of reaction kinetics systems.
- Reachability, reachability analysis for hybrid systems. Reachability in continuous systems - piece-wise linear systems, finite quotients.
- Controllability. Open-loop and closed-loop control, black-box control, model-based control, controller synthesis. System observability and identifiability.
- Parameterization, parameter uncertainty, sensitivity analysis. Tools for parameter estimation, system identification.
- Methods for system comparison: system equivalence, bisimulation and approximative bisimulation. Robustness analysis.
- Explained methods will be demonstrated in the form of practicals especially from the domain of computational systems biology. Tools from the following set will be employed: MATLAB/Octave, COPASI, GNA, SpaceEx/PHAVer, Ariadne.
- recommended literature
- P. Tabuada. Verification and Control of Hybrid Systems: A Symbolic Approach. Springer, 2009. xv, 202 p. ISBN 978-1-4419-0223-8.
- J.H. van Schuppen. Control and System Theory of Positive Systems, CWI Lecture notes, 2007.
- VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia, Pa.: Society for Industrial and Applied Mathematics, 2006. xii, 309. ISBN 0898716128. info
- LYNCH, Stephen. Dynamical systems with applications using MATLAB. Boston, Mass.: Birkhäuser, 2004. xv, 459. ISBN 3764343214. info
- ŠTECHA, Jan and Vladimír HAVLENA. Teorie dynamických systémů : přednášky. 2. vyd. Praha: Vydavatelství ČVUT, 2002. 247 s. ISBN 8001019713. info
- ARROWSMITH, David K. and C. M. PLACE. An introduction to dynamical systems. New York, N.Y.: Cambridge University Press, 1990. 423 s. ISBN 0521316502. info
- Teaching methods
- lectures, exercises
- Assessment methods
- 50% project, 50% written exam
- Language of instruction
- Further Comments
- Study Materials
The course is taught once in two years.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/fi/autumn2019/IV120