Robust Distributed Model Predictive Control of Constrained Continuous-Time Nonlinear Systems: A Robustness Constraint Approach

Abstract

Due to the ubiquitous existence of external disturbances, the design of distributed control algorithms with robustness is an urgent demand for multi-agent system applications. This technical note investigates the robust distributed model predictive control (MPC) problem for a group of nonlinear agents (subsystems) subject to control input constraints and external disturbances. A robustness constraint is proposed to handle the external disturbances. Based on this, a novel robust distributed MPC scheme is designed for the overall agent system. Furthermore, the feasibility of the robust distributed MPC scheme and the robust stability of the overall agent system are analyzed, respectively. The conditions under which the proposed MPC is feasible and the overall agent system is robustly stabilized are established. Finally, the application of the robust distributed MPC to a group of cart-damper-spring systems verifies the theoretical results.