Grigore Stamatescu

Grigore Stamatescu

Professor at UPB

Teaching

Description: The Information Processing course covers a range of fundamental knowledge on statistics elements, probabilities and data processing, in an engineering context. These include, selectively: statistical indicators, probability distributions, parameter estimation methods and verification of statistical hypotheses and regression methods. Methods for identifying and handling outliers are presented. Rigorous methodologies and best practices for data set processing, classification of data sources and types, including open data sets and public modeling and prediction competitions, preliminary data processing/pre-processing as well as data visualization and presentation techniques towards diverse audiences are discussed. Applications are carried out in interactive Matlab and Python programming environments.

Keywords: applied statistics, probability theory, exploratory data analysis, regression methods, outlier handling, data science

Description: The main objective of the Intelligent Measurement Systems course is to present the main design concepts and applications of networked embedded systems in environmental, urban, industry and energy monitoring, as fundamental building blocks of the new Internet of Things (IoT) and Cyberphysical Systems (CPS) concepts. Node-level aspects: sensor selection, energy issues and local data processing, and network-level aspects: wireless communication, localization, mobility, routing and distributed algorithms, are addressed in detail. The social implications of the widespread adoption of these systems are also discussed. Practical simulation applications are developed using the CubCarbon hybrid IoT environment as well as experimental implementations on a dedicated WSN test bed.

Keywords: networked embedded systems, sensors, distributed data processing, wireless sensor networks, internet of things

Description: The course on Control Engineering (Regelungstechnik) consists of an introduction to the theory of linear dynamic systems and the design of control systems, with modeling and simulation applications and the presentation of pilot installations. Topics related to the mathematical modeling of physical systems and the study of their behavior in the time and frequency domains are addressed, based on test signals. The stability of continuous linear systems is defined and evaluated. Methods of analysis and synthesis of the regulation and design loops of P- / PI- / PID type regulators are presented, including the optimization of tuning parameters, with applicability in the management of industrial processes and intelligent embedded systems. Modern software tools are used e.g. development environment for MATLAB / Simulink technical computing and interactive teaching methods.

Keywords: modelling and simulation, time analysis, frequency analysis, stability, automatic control systems, matlab / simulink

Description: The course on Control Engineering II is a continuation of the discipline of Control Engineering (Regelungstechnik I). The method of analysis and design of systems based on root locus is presented. An introduction is made in the field of state space and an analysis and synthesis of nonlinear systems in the domain of frequency and in state space. The controllability and observability properties of the systems are described and evaluated. Intelligent techniques for control of industrial processes using fuzzy logic, neural networks and genetic algorithms are also presented. The project assignment developed during the course integrates the knowledge gained in a unitary approach, with practical applicability through appropriate software tools: MATLAB Control System Toolbox, SISO Tool, Fuzzy Logic Toolbox.

Keywords: root locus, state space, multivariable system, nonlinear systems, intelligent control systems

Keywords: informatics, programming, python, data structures and algorithms, object oriented programming