Complex systems are present everywhere in our environment: internet, electricity distribution networks, transport networks. This systems have as characteristics: a large number of autonomous entities, dynamic structures, different time and space scales and emergent phenomena. This thesis work is centered on the problem of control of such systems. The problem is defined as the need to determine, based on a partial perception of the system state, which actions to execute in order to avoid or favor certain global states of the system. This problem comprises several difficult questions: how to evaluate the impact at the global level of actions applied at a global level, how to model the dynamics of an heterogeneous system (different behaviors issue of different levels of interactions), how to evaluate the quality of the estimations issue of the modeling of the system dynamics. We propose a control architecture based on an " equation-free " approach. We use a multi-agent model to evaluate the global impact of local control actions before applying the most pertinent set of actions. Associated to our architecture, an experimental platform has been developed to confront the basic ideas or the architecture within the context of simulated "free-riding" phenomenon in peer to peer file exchange networks. We have demonstrated that our approach allows to drive the system to a state where most peers share files, despite given initial conditions that are supposed to drive the system to a state where no peer shares. We have also executed experiments with different configurations of the architecture to identify the different means to improve the performance of the architecture.
