Abstract: It is familiar that there are two basic approaches to system modeling. The first one consists in using mathematical formulas and physical principles (a causality principle, different forms of conservation laws, power balance relations, etc.) in order to describe appropriate system behavior. It has successfully been used in many fields of science and engineering so far. However, there are also situations where physical laws are not known or cannot be expressed in a proper mathematically exact form. In that case the second basic so called cybernetic approach to system modeling can be turned. It is based on identification methods working in terms of experimentally gained data. It is possible to divide the identification methods into two groups: parametric and non-parametric, respectively. If any prior information about a system structure is not available then one of non-parametric procedures has to be chosen for system identification. On the other hand, imagine that a physical structure of an investigated system would be known. In such cases some of available parametric methods can be used and consequently more adequate results from the physical correctness point of view should be obtained. Unfortunately, any reliable explicit knowledge about a physical system structure is more likely an exception than a rule. Therefore, a system structure is mostly chosen ad hoc only behalf of heuristic arguments. Subsequently it has to be verified whether obtained quantitative results are not in conflict with obvious qualitative expectations concerning regular system behavior and/or results of additional experiments performed on a real system. The lecture is organized as follows: The first part is devoted to the problem of physical correctness of systems models and new concept of the state space energy is introduced and a generalized form of the theorem called the Lyapunov-Tellegen/s principle is presented. In the second part there are demonstrated some of application concerning problem of the state space energy including continuous and discrete-time systems and also chaotic systems. The nonlinear stability analysis by means of the proposed state space energy based method is also discussed. Results of simulation examples will also presented.

Brief Biography of the Speaker:
Milan Stork received the M.Sc. degree in electrical engineering from the Technical University of Plzen, Czech Republic at the department of Applied electronics in 1974. He specialized in electronics systems and control in research institute in Prague. Since 1977 he worked as lecturer on University of West Bohemia in Plzen. He received Ph.D. degree in automatic control systems at the Czech Technical University in Prague in 1985. In 1997, he became as Associate Professor. From 2007 he is full professor at the Department of Applied Electronics and Telecommunication, faculty of electrical engineering on University of West Bohemia in Plzen, Czech Republic. He has numerous journal and conference publications. He is member of editorial board magazine "Physician and Technology". His research interest includes analog/digital linear, nonlinear and chaotic systems, control systems, signal processing and biomedical engineering, especially cardiopulmonary exercise systems.