S2: System Modeling and Analysis

Lectures: O. Kosmidou, A. Protopapas, B. Papadopoulos.
Academic Credits: 3.

Description:
The objective of the course is to present and establish several techniques for model formulation and system analysis. Deterministic systems: The concept of mathematical model. Types of mathematical models. Development of models from experimental data. Simulation, validation, and acceptance of a mathematical model. The concept of system analysis using mathematical models. The concept of system stability. Stability criteria. Time response. Characteristics of transient response. Error in steady state. The significance of poles in time response. Examples - Exercises. Fuzzy systems: Introduction to fuzzy logic. Operation rules for fuzzy systems. Stochastic systems: Review of multivariable theory of probability. State estimation of static systems. Bayes method of least square error. Maximum Likelihood Method. Uncertainty propagation in linear systems in state space form in discrete time. State estimation of dynamic systems - Kalman filter. Interpretation and examples, asymptotic behavior, the role of controllability, observability and stability.