Systems with high steady-state multiplicity and rich dynamic behavior are difficult to investigate
using conventional reductionist methods. A network of more than five reactors hosting cubic
autocatalytic reactions may potentially have more than 102 steady states and many distinct
dynamic regimes, all for the same parameter set. This paper discusses how the static complexity
of such systems can be measured to give a holistic picture. To achieve this, stochastic simulations
were performed to statistically determine the bifurcation structure of the system, and the
gathered information is summarized using a measure akin to fractal dimension. With this
measure, the growth of static complexity is investigated as a function of the network size.
Two types of nonlinear feedback control schemes are introduced and analyzed for their capability
of recovering the original state of an isothermal continuous-flow stirred tank reactor with one
robust cubic autocatalytic species, perturbed by a temporary disturbance of an invading cubic
autocatalytic species in the inflow. The control objectives are to eliminate the invading species
from the system and to restore the original state of the host species. The extent of applicability
of the control design to different nonrobust invading species is studied, when the controller is
tuned for a specific invader. Moreover, a time-delay feature is suggested in one of the control
schemes developed to achieve the control objectives in systems with poor detection of invading
species.
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.
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