Control of interconnected systems with distributed model knowledge

This thesis presents new and innovative approaches for the analysis and control of interconnected dynamical systems. Their main applications are distributed stability analysis and optimal control design. The main contribution is that the developed methods do not rely on a centralized decision maker and are based on distributed model knowledge. The key to the distributed decision making is the use of modern distributed optimization techniques, and the behavior of the presented approaches is analyzed thoroughly both in analytical and numerical fashion.