Nonlinear control of large scale complex systems using convex optimization tools and self-adaptation

Based on recent advances on convex design for Large-Scale Control Systems (LSCSs) and robust and efficient LSCS self-tuning/adaptation, a methodology is proposed in this paper which aims at providing an integrated LSCS-design, applicable to large-scale systems of arbitrary scale, heterogeneity and complexity and capable of: 1) Providing stable, efficient and arbitrarily-close-to-optimal LSCS performance; 2) Being able to incorporate a variety of constraints, including limited control constraints as well as constraints that are nonlinear functions of the system controls and states; 3) Being intrinsically self-tunable, able to rapidly and efficiently optimize LSCS performance when short-, medium- or long-time variations affect the large-scale system; 4) Achieving the above, while being scalable and modular. The purpose of the present paper is to provide the main features of the proposed control design methodology.