Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
Prof. Adrian Olaru finished the University
Politehnica of Bucharest, Faculty of Machines and Manufacturing
Systems, Romania, in 1974, head of promotion. From 1974 until
1990 he worked as a designing engineer at the "Optica Romana"
Enterprise, also being an associate assistant at the Faculty of
Machine-Building Technology of the Polytechnic Institute of
Bucharest. In 1990 Prof. Adrian became an appointed lecturer at
the Faculty of Technological Systems Engineering and Management,
the Machine-Tools Department. Now, he is university full
professor, and teaches the following courses: Industrial Robots
Dynamics, LabVIEW application in modeling and simulation of the
dynamic behavior of robots, Technological Transport Systems,
Electrohydraulic Servosystems, Analyze and Syntese of
Electrohydraulic Servosistems for Industrial Robots, Personal
and social robots and Vibration of the virtual prototypes of
industrial robots. Prof. Adrian Olaru has published over 160
national and international papers concerning modeling and
simulation of hydraulic power system, technological transport
systems, electrical and hydraulic servo systems and dynamic
behavior of industrial robots. For recent relevant details, see
the publication list and the web page. He also has substantial
contribution for over than ten technical books. Prof. Adrian
Olaru was invited professor of the prestigious universities
arround the world and the invited speacker at the different
international conferences from Slovakie, France, Italy, China,
India, Iran, Poland, Autrich, Rusian Federation, United Arab
Emirates, Turkie, Croatie. He was coopted each year in the more
than 20 International Technical Committees and like general
co-chair from the different international conferences arroun the
world: USA, Australy, India, United Arab Emirates, Porto Rico,
China, Singapore, Malayesia, Japan, Tayland, Slovaky, Czech
Speech Title: Virtual LabVIEWTM
Instrumentation for Simulation and Optimisation of the Robot
Abstract: In the assisted researching
of the dynamic behaviour of industrial robots an important role
plays modelling, simulation and optimisation with virtual
LabVIEWTM instrumentation. Virtual instrumentation easy provides
comparison of theoretical with experimental results and could be
established the conditions to adjust and validate the
mathematical models. The paper shows numerous virtual
instruments and some case study to optimise the vibration and
the motion of robots end-effecter in the 3D space, by using the
assisted simulation and animation after solving the inverse
kinematics by proper methods.
Prof. Bogdan Rosa
Institute of Meteorology and Water Management - National
Research Institute, Poland
Bogdan Rosa received his M.Sc. in physics from the University of Warsaw in 2000, followed by the Ph.D. in 2005. The subject matter of his Ph.D. research concerned theoretical and laboratory investigations of the airborne ultra-fast thermometer. This tool provides reliable clear-air and in-cloud temperature measurements with unprecedented spatial resolution, down to a few centimeters. Afterwards, he spent 3 years as a postdoctoral fellow at the University of Delaware, where he was involved in developing computational tools to study collision rates and growth of droplets in atmospheric clouds. This is an important and poorly-understood problem in cloud physics. During the postdoctoral fellow he spent a couple months at National Center for Atmospheric Research. Since 2009, Prof. Rosa is working at the Institute of Meteorology and Water Management - National Research Institute. Apart of modeling of microphysical processes in turbulent clouds his current projects involve adaptation of the numerical model EULAG into a operational weather prediction model (NWP) of the European COSMO consortium. He published close to 30 paper in peer-reviewed atmospheric science journals and more than 100 papers in conference proceedings. He built upon his expertise in atmospheric processes by working with scientists from Germany, Iran, China, USA, Venezuela and Japan. He was the project leader and principal investigator of several international projects, such as adaptation of fluid solver to high-performance computing platforms, NWP with GPU, high resolution DNS. He is reviewer for the following journals: New Journal of Physics, Physics of Fluids, Fluid Dynamics Research, International Journal of Modeling and Optimization.
Speech Title: Dynamics of Inertial
Particles in Turbulent Flows
Abstract: In recent years,
pseudo-spectral direct numerical simulations (DNS) have emerged
as an important research tool for studying statistics,
structure, and dynamics of small-scale turbulence and dynamics
of suspended inertial particles. Such studies are used to
address a number of fundamental questions in applications such
as pipeline pneumatic transport, spray combustion, reactions in
nuclear systems or warm rain formation. Modeling of these
processes is a quite challenging task due to the wide range of
scales involved (both spatial and temporal). Interaction of the
inertial particles with turbulent flows affects their spatial
distribution, the settling velocity, and consequently influences
the collision rate.
In this talk the main focus is on the kinematic and dynamic
collision statistics of inertial particles relevant to cloud
droplets (of radius from 10 to 60μm) in a typical turbulent
cloud. Collision–coalescence of cloud droplets is a necessary
step for the development of warm rain, namely, the
transformation of small cloud droplets into raindrops. Warm rain
processes account for about 31% of the total rain fall and 72%
of the total rain area in tropics.
The purpose of this study is to quantify the effects of air
turbulence on the growth of cloud droplets during warm rain
initiation. Turbulence can enhance the rate of
collision–coalescence and as such provides a mechanism to
overcome the gap between the diffusional growth and the
gravitational collision–coalescence mechanism. Several specific
issues related to geometric collisions (without droplet–droplet
aerodynamic interaction) of the same-size particles will be
discussed. These include: the effect of the large-scale forcing
mechanisms, the effect of the flow Reynolds number or
equivalently the range of flow scales represented in DNS and the
role of gravity. A thorough analysis of these effects is
necessary for developing better parameterizations for numerical
weather prediction models which, in turn, will allow to develop
more accurate weather forecasts and deepen our knowledge of the
global climate change.
Prof. Wojciech Grega
AGH University of Science and Technology in Krakow, Poland
Wojciech Grega received his M.Sc. in
electrical engineering and Ph.D. and D.Sc. degrees in automatic
control from AGH University of Mining and Metallurgy in Krakow.
Currently, he is a full professor of AGH in Krakow: digital
control, optimisation methods, distributed control and
industrial control systems. He as a author and co-author of more
than 150 papers and books. He has been the coordinator or main
researcher in 19 national and international projects; the vice
dean of the Faculty in 1994, the head of the Control Laboratory
since 2000, the head of the Faculty Commission for Education
from 2001 to 2009. He is a elected member of the European
Association for Education in Electrical and Information
Engineering; IEEE Society Member; European Union Academic
Expert; KIC InnoEnergy Poland+ Educational Director.
On-Line Implementation of Optimization Methods for Industrial Control Systems
Abstract: A large potential for improvement of the manufacturing efficiency and end product quality lies in the implementation of advanced control algorithms as well as optimization algorithms with the configuration presented in the figure (see below). This control system employs several hierarchy levels:
At the process optimisation level the quality indices, such as steady state energy consumption, are selected for an optimisation problem.
The goal of this optimization procedure is to drive the operating point towards the actual plant optimum despite of inevitable structural and parametric model mismatch. Its solution are set points for lower level. Multivariable and predictive process control algorithms (MPC) use the operating point specification provided by the optimiser to develop optimal trajectories for multiple input signals. The aim is to achieve optimal time dependent behaviour of multiple outputs delivered to the lower level.
PI or PID cascaded controllers are implemented at the direct control level.
The on -line optimization level is an extension of feedback control system and consists of subsystems for measurement validation, steady-state detection, process model updating and model-based optimization.
The optimization level is a model-based approach that consists of model adaptation using available measurements and numerical optimization which is performed on the updated model. The process model is embedded within a nonlinear programming (NLP) problem that is solved repeatedly.
In the presentation the subsystems of the optimization level will be described. Special attention will be devoted to trade-off between model complexity and calculation time. For on-line implementation of optimization methods model calculation time is strictly limited. A model size reduction must be implemented in order to ensure a simulation time which is sufficient for real-time control.
The control and optimization of the glass melting and conditioning process will be provided as an implementation example.