In a complex dynamic system the centralised control and local monitoring of system behaviour is not achievable by scaling up simple feedback adaptation and control models. This paper proposes using a variety of concepts from distributed artificial intelligence (DAI) to logically model an abstract system control using adaptable agent federations to induce self-organisation in a swarm type system. The knowledge acquisition and updates are handled through a modal logic of belief for team dynamics and the system as a whole evolves to learn from local failures that have minimal impact on the global system. Self-governance emerges from innate (given) action thresholds that are adapted dynamically to system demands. In this way it is shown that such a system conforms to the prerequisites that have been specified as necessary for a system to exhibit self-organisation and the intrinsic benefits of agent teamwork are established for a robust, reliable and agile system. The approach is illustrated by looking at team formation in a swarm scenario from a proposed NASA project. The Situation Calculus is used to formalise the dynamic nature of such systems with a dynamic logic implementation to reason about the ensuing programs. Subsequently the model is encoded using the Neptune scripting language and compiled to an object-oriented system for its deployment on distributed systems architecture.