Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2

simulation environment Related Publications

2 Graphical Environment for Modeling Control Systems in Full Scope Training Simulators

Authors: Guillermo Romero-Jiménez, Víctor Jiménez-Sánchez, Edgardo J. Roldán-Villasana

Abstract:

This paper describes the development of a control system model using a graphical software tool. This control system is part of an operator training simulator developed for the National Training Center for Operators of Ixtapantongo (CNCAOI, acronym according to its name in Spanish language) of the Mexico-s Federal Commission of Electricity, CFE). The Department of Simulation of the Electrical Research Institute (IIE) developed this simulator using as reference the Unit I of the Combined Cycle Power Plant El Sauz, located at the centre of Mexico. The first step in the project was the developing of the Gas Turbine System and its control system simulator. The Turbo Gas simulator was finished and delivered to CNCAOI in March 2007 for commercial operation. This simulator is a high-fidelity real time dynamic simulator built and tested for accurate operation over the entire load range. The simulator was used primarily for operator training although it has been used for procedure development and evaluation of plant transients.

Keywords: Operators training, Power plant simulator, simulation environment

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1 Using Emotional Learning in Rescue Simulation Environment

Authors: Caro Lucas, Maziar Ahmad Sharbafi, Abolfazel Toroghi Haghighat, Omid AmirGhiasvand, Omid Aghazade

Abstract:

RoboCup Rescue simulation as a large-scale Multi agent system (MAS) is one of the challenging environments for keeping coordination between agents to achieve the objectives despite sensing and communication limitations. The dynamicity of the environment and intensive dependency between actions of different kinds of agents make the problem more complex. This point encouraged us to use learning-based methods to adapt our decision making to different situations. Our approach is utilizing reinforcement leaning. Using learning in rescue simulation is one of the current ways which has been the subject of several researches in recent years. In this paper we present an innovative learning method implemented for Police Force (PF) Agent. This method can cope with the main difficulties that exist in other learning approaches. Different methods used in the literature have been examined. Their drawbacks and possible improvements have led us to the method proposed in this paper which is fast and accurate. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is our solution for learning in this environment. BELBIC is a physiologically motivated approach based on a computational model of amygdale and limbic system. The paper presents the results obtained by the proposed approach, showing the power of BELBIC as a decision making tool in complex and dynamic situation.

Keywords: rescue, multi-agent system, robocup, simulation environment, Emotional learning

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