Agent-based system for reconfiguration of distributed chemical reactor network operation

Abstract

Control of spatially distributed systems is a challenging problem because of their complex nature, nonlinearity, and generally high order. Agent-based control structures provide a powerful tool for managing distributed systems by utilizing local and global information obtained from the system. A hierarchical, agent-based system with local and global control agents is developed to control networks of interconnected chemical reactors hosting multiple autocatalytic species. The global controller agent dynamically updates the objective of local control agents as the reactor network conditions change. The case illustrated in this paper is to change the dominant species in one CSTR by modifying feed and interconnection flow rates with the constraint of shortest path possible, which causes the least amount of changes in the whole network. The agent-based system and the reactor networks are implemented using the agent-based system development framework RePast.

An agent-based simulation framework for cognitive radio studies

“…The entire framework was programmed and developed using Repast Simphony [28], which is a free and open source agentbased modeling toolkit that simplifies model creation and use. This choice was dictated by previous experience with the tool, as well as expected testing of MADCABS multi-agent control system [32] that was developed using the same tool.…”

Self-Organizing Agent-Based Grade Transition in Distributed Chemical Reactor Networks

“…Tetiker et al proposed two different hierarchical agent-based frameworks for the problem of changing the spatial distribution of autocatalytic species in a CSTR network, given the initial and the final configurations of the system (Tetiker, 2006a;Tetiker, 2006b). The first framework uses a centralized approach where a global planner agent observes the whole network, calculates the optimum path to be followed to move the system from one spatial distribution to another and assigns local objectives to local agents.…”