8th IEEE International Conference on Intelligent Engineering Systems


FINAL PROGRAM
It is guaranteed to include the final paper into the conference proceedings in case of registration and payment in advance.

Plenary Speakers

Plenary Speaker I

Professor János Somló

Budapest University of Technology and Economics, Hungary

Control Problems of Production Processes
Abstract
Structure and processes of Flexible Manufacturing Systems (FMS) is discussed. Three of the fields from different subsystems is chosen where control problems have dominant role.
These are:
1. Cutting process optimisation.
2. Optimal robot motion planning.
3. Hybrid Dynamical (Switched Server) Approach to FMS scheduling.
All the mentioned are based on original contributions of the author.
The topics include:
1. General method of cutting process optimisation. Adaptive Control Optimization (ACO) of machine tools.
2. General method of optimal cruising trajectory planning for robots. Four different solution of motion planning problems. LabVIEW based OSA (Open System Architecture) robot control device. Assimptotically stable MRAC (Model Reference Adaptive Control) of robots.
3. Hybrid Dynamical Approach (HDA) to FMS scheduling. FMS scheduling as a nonlinear dynamical control problem. Continuous system formulation. Stability. Periodic motions. Discrete system simulation approach.
New results:
a. Demand rates determination method reflecting practical requirements.
b. The controlled buffer technique.
c. Periodic and transient schedules.
d. Piece-wiese constant demand rates.


Plenary Speaker II

Professor Antal K. Bejczy

Senior Research Scientist
JPL/CALTECH
Pasadena, California, USA
antbej@earthlink.net

Intelligent Robotic Aids Help Mars Exploration
Abstract
Today scientists follow the “water trail” strategy to search for possibilities of life forms in our Solar system. This simple scientific strategy motivates the Mars rover missions. The Mars Global Surveyor and Mars Odyssey Orbiters have revealed many surface features on Mars that strongly appear to have been shaped by running water that has since disappeared, and possibly buried as layers of ice just under the planet’s surface. The first Mars rover mission Pathfinder in 1997 with the small Sojourner rover and the ongoing Mars Exploration Rover (MER) mission in 2004 with the twin rovers Spirit and Opportunity have been designed to be intelligent robotic aids to geologists suited to “reading the rocks” littered across Martian surface, in order to understand the mysterious history of water, and even of possible life-friendly ancient environments there. The presentation will outline the MER mission’s science objectives, describe the engineering features of the twin - Spirit and Opportunity – rovers and their science instruments, and quote a few interesting and illustrative findings obtained by scientists through these twin rovers. A brief CD-ROM disc will graphically show the journey of the twin rovers from Earth to Mars and some of their activities on Mars. The presentation will conclude with discussion of future intelligent robotic capability needs and NASA mission plans for continued Mars exploration.


Plenary Speaker III

F.G.Filip

Member of the Romanian Academy
National Institute for R&D in Informatics, Bucharest and the Romanian Academy

Intelligent Decision Support Systems for Industrial Applications
Abstract
A Decision Support System (DSS) is an anthropocentric, adaptive, and evolving information system meant to implement some of the functions of a possible "human support system" (or team) that would be otherwise needed to help the decision-maker to overcome his/her limits and constraints he/she might face when approaching decision problem that count. In industrial milieu the DSS is frequently utilised to facilitate solving problems under time pressure when " crisis" situations show up.
The paper addresses the following issues:
1. Typical decision problems in industrial applications.
2. Limits and constraints of the human decision -maker.
3. Dangers and "ironies" of automation.
4. DSS: definitions and main attributes.
5. Classifications
6. "Division of labour" within intelligent DSS with mixed knowledge (numeric models and AI-based modules)