We present a conceptual model of an adaptive control system, capable of adaptation to emergent collective behavioral properties of the controlled object, as it reacts with some unknown environment. A system's behavior can be sufficiently modeled if three, and only three, aspects of the behavior can be modeled. These are the syntax, the semantics and the pragmatics of the behavior. As the system interacts with the unknown environment, new behaviors emerge, when the mutual interactions and relations between the three aspects gets altered. We use a state observer to reconstruct the state vectors to model the emergent state trajectories that map onto emergent behavior. A dynamic performance evaluation is proposed to take into account for the new behaviors. This performance evaluation is also a fitness measure for a Genetic Algorithm (GA) which evolves new rule sets to be used as a fuzzy rule base for a fuzzy control system.
展开▼
