Abstract

Classical theory for multi-variable control synthesis suffers from a severe lack of scalability. Not only does the computational cost for derivation of optimal controllers grow rapidly with state dimension, but also implementation of the resulting controllers becomes unmanageable in large networks due to requirements for communication, computation and memory. Because of this situation, considerable research efforts have recently been devoted to development of scalable and structure preserving methods for design and implementation of networked control systems. In this lecture, we will present a class of networked control problems for which distributed controllers can be proved to achieve the same performance as the best centralized ones. The control objective is stated in terms of frequency weighted H-infinity norms. This makes it possible to combine disturbance rejection at low frequencies with robustness to high frequency measurement noise and model errors. An optimal controller is given, which is structure preserving in the sense that it has the same interconnection structure as the plant.