Multiobjective optimization in control with communication for decentralized discrete-event systems

The trade-off between the cost and accuracy of a decentralized discrete-event control solution with synchronously communicating controllers is explored as a multiobjective optimization problem. We examine a class of problems where communication protocols are necessary to realize the exact control solution. In certain circumstances, it may be advantageous, from a cost perspective, to reduce communication, but incur a penalty for synthesizing an approximate control solution. A widely-used evolutionary algorithm (NSGA-II) is adapted to examine the set of Pareto-optimal solutions that arise for this family of decentralized discrete-event systems.