César Bravo

A MULTI-AGENT SYSTEM FOR THE MANAGEMENT OF ABNORMAL SITUATIONS IN AN ARTIFICIALLY GAS-LIFTED WELL

Concerning industrial automation, the management of abnormal situations becomes more important everyday. The ability to detect, isolate, and handle abnormal situations in industrial installations, could save huge amounts of money which is normally invested in reparations and/or wasted because of unjustified stoppage of processing plants. In this work, a system for the management of abnormal situations in an artificially gas-lifted well based on agents Abnormal Situations Management System (ASMS) is developed, which is part of the architecture of the industrial automation based on multi-agents systems (SADIA) proposed in Bravo, Aguilar, and Rivas (2004). This agent is based on the intelligent distributed control system based on agents (IDCSBA) reference model proposed in Aguilar, Cerrada, Mousalli, Rivas, and Hidrobo (2005). The MASINA methodology (Aguilar, Hidrobo, and Cerrada 2007) is used in matters of analysis, design, and implementation.

Design of an industrial automation architecture based on multi-agents systems

Abstract New paradigms in industrial automation aims towards intelligence distribution among components of the productive process and through the integration of several systems and applications in the companies, searching processes improvement, supporting decision-making tasks by real time information available, reliable and opportune. This work proposes industrial automation architecture based on multi-agents systems and uses the framework SCDIA to describe this architecture.

Multiagent systems for production planning in automation

The production planning represents a key activity in the performance of the industry, reason why the necessity of applications that offer support to this activity, that allow to reach the goals of production with the maximum benefit. The proposal of this work is to develop a Multiagent Systems (MAS) for the Production Planning in Industrial Automation (specifically, in continuous processes). In addition, we present an application of our proposal in a process of petroleum production based on the Artificial Gas Lift Method.