Narrow Results

In this paper, we present a complete design framework for an adaptive multiple agent fuzzy constraint-based controller (MAFCC) based on fuzzy penumbra constraint processing in each fuzzy constraint subnetwork collaborating with a connected constraint network and its corresponding semantic modeling in a first-order predicate calculus (FOPC) language, with application to a complex hydraulic system. The concept of “multiple agent” and “fuzzy constraint subnetwork” in a complex control system is introduced and some basic definitions of penumbra fuzzy constraint processing in a constraint subnetwork and the collaboration with an overall connected constraint network and its semantic modeling are addressed. As a result, a human agent interacts with system agents and allows the constraints to be added or deleted on-line according to the constraints imposed from the outside environment. Near-optimal system performance is accomplished by restricting all the penumbra constraints to be satisfied in each constraint subnetwork simultaneously which are interconnected as a result of constraints that exist between each of them. Following the principle of constraint satisfaction and fuzzy local propagation reasoning, each individual system agent is now constrained to behave in a certain fashion as dictated by the overall constraint network. In addition, the constraint network in MAFCC system provides an update strategy which makes a real time adaptive hydraulic control for all 20 cities possible.