Distributed Nonlinear Control Design using Separable Control Contraction Metrics
It offers a scalable distributed control design for large-scale nonlinear systems, addressing a key bottleneck in networked control.
This paper extends control contraction metrics to distributed nonlinear control, providing convex conditions for synthesizing controllers that use only local and neighbor information. The method is demonstrated on a vehicle platooning problem and a network with over 1000 states.
This paper gives convex conditions for synthesis of a distributed control system for large-scale networked nonlinear dynamic systems. It is shown that the technique of control contraction metrics (CCMs) can be extended to this problem by utilizing separable metric structures, resulting in controllers that only depend on information from local sensors and communications from immediate neighbours. The conditions given are pointwise linear matrix inequalities, and are necessary and sufficient for linear positive systems and certain monotone nonlinear systems. Distributed synthesis methods for systems on chordal graphs are also proposed based on SDP decompositions. The results are illustrated on a problem of vehicle platooning with heterogeneous vehicles, and a network of nonlinear dynamic systems with over 1000 states that is not feedback linearizable and has an uncontrollable linearization