Distributed Model Predictive Control for Reconfigurable Systems With Network Connection

Abstract

This article proposes a distributed model predictive control (DMPC) strategy for a class of large-scale systems composed of several interacting subsystems. When a certain subsystem is required to be removed or inserted, the topology change of the system network can lead to the infeasibility of interacting local controllers due to the existence of the interactions among subsystems. In this article, the interactions among subsystems are presented as state trajectory estimations of interacting subsystems, and the estimations are involved in each local MPC. To deal with the influence resulted from the change of system topology, optimization schemes for removal and plugging-in are designed and employed in the proposed strategy. They optimize related subsystems’ reference trajectories, which are used to approximate the interacting state trajectories here, to reduce the time it takes to drive the system states and reference trajectories to a region. This region ensures that the system topology change can be conducted with all controllers having feasible solutions. The proposed DMPC algorithm has the following characteristics: 1) all the optimization problems in each MPC are solved in a noniterative manner and each controller only communicates with its neighbors and 2) it guarantees the feasibility of all controllers throughout the topology change process and the convergence of the system after the topology change. Simulation results show the effectiveness of the proposed DMPC algorithm. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The DMPC algorithm proposed in this article is designed for networked systems where certain subsystems may be removed or inserted. The purpose is to obtain a fast response to this topology change of system. An integrated algorithm is provided for the application of the strategy. First, the parameters of the MPCs are initialized. Then, before the command of a switch in topology is given, local controllers for normal situations provide the real-time inputs. Once the switch of topology is commanded, additional optimization problems are solved in the related subsystems’ controllers to guarantee the feasibility of removal or plugging-in operation. The optimization problems involved in each MPCs can be solved by adopting efficiently quadratic programming solvers supported by MATLAB. Note that although the topology change is commanded, all the subsystems are still operated normally until the topology change is conducted. In general, the strategy introduced in this article can be applied to control a class of large-scale networked systems, where each subsystem-based controller can exchange information with its neighbors.