Agent-Based Control of Spatially Distributed Chemical Reactor Networks

Large-scale spatially distributed systems provide a unique and difficult control challenge because of their nonlinearity, spatial distribution and generally high order. The control structure for these systems tend to be both discrete and distributed as well and contain discrete and continuous elements. 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. Traditionally, research on control of nonlinear distributed processes has focused on distributed parameter systems involving mathematically complex model reduction and controller synthesis methodologies. So-called hybrid control systems combine process dynamics and discrete control elements through the use of multiple linear models at different operating points. One alternative approach is based on a hierarchical agent-based system with local and global control structures that has been demonstrated on a network of interconnected continuous stirred tank reactors (CSTRs). Reactor networks exhibit highly complex behavior, with multiple steady state operating regimes, and have a large pool of candidates for manipulated variables. We use autocatalytic reactions in these networks to formulate surrogates for predator-prey, virus propagation in a distributed population, multiple species of animals that rely on the same resources, or chemical manufacturing problems.