In this paper, a complete design framework for an adaptive multiple agent fuzzy constraint-based controller based on fuzzy penumbra constraint processing in each fuzzy constraint subnetwork collaborated by a connected constraint network and its corresponding semantic modeling in a first-order predicate calculus (FOPC) language applied in a complex hydraulic system are presented. 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. The partitioning of a complex problem into subproblems is performed by employing a ``multiple agent'' concept. In this concept, the decomposition of a complex system is based on assigning each agent specific objects subjected to the constraints to act on. This idea contribute significantly to the domain of problem with great complexity due to the fact of collaboration of each agent and the assertion and deletion of its constraints that occur in the world model. As the 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 outside environment. An optimal system performance is accomplished by restricting all the penumbra constraints to be satisfied in each constraint subnetwork simultaneously which are interconnected as a results 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.