Distributed Quasi-Nonlinear Model Predictive Control with Contractive Constraint

Abstract

An approach to low complexity distributed MPC of nonlinear interconnected systems with coupled dynamics subject to both state and input constraints is proposed. It is based on the idea of introducing a contractive constraint in the centralized NMPC problem formulation, which would guarantee the closed-loop system stability when using a small prediction horizon. Particularly, the one step ahead NMPC problem is considered. Further, a quasi-NMPC method is developed, which is based on a sequential linearization of the nonlinear system dynamics and finding distributedly a suboptimal solution of the resulting convex Quadratically Constrained Quadratic Programming problem. The suggested approach would be appropriate for distributed convex NMPC of some cyber-physical systems, since it will reduce the complexity of the on-line NMPC computations, simplify the software implementation, and reduce the requirements for available memory. The proposed method is illustrated with simulations on the model of a quadruple-tank system.