AGENT-BASED CONTROL FOR DYNAMIC CONFIGURATION OF SPATIALLY DISTRIBUTED NETWORKS

Abstract

Large-scale spatially distributed systems provide control challenges because of their nonlinearity, spatial distribution, and generally high order. The control structure for these systems tends to be both discrete and distributed. A layered control structure interfaced with complex arrays of sensors and actuators provides a flexible supervision and control system that can deal with local and global challenges. An adaptive agent-based control structure is presented whereby local control objectives may be changed in order to achieve the global control objective. Information is shared through a global knowledge environment that promotes the distribution of ideas through reinforcement. The performance of the agent-based control approach is illustrated in a case study where the interaction front between two competing autocatalytic species is moved from one spatial configuration to another. The multi-agent control system is able to effectively explore the parameter space of the network and intelligently manipulate the network flow rates such that the desired spatial distribution of species is achieved.