A Collision-free Communication Scheduling for Nonlinear Model Predictive Control

In this paper, we propose a framework to generate communication schedulings for nonlinear model predictive control. The proposed method considers the case where multiple plants share a communication network, and the goal is to pre-plan for each plant a timing to communicate with the controller to solve an optimal control problem. The desired communication schedulings are generated such that: (i) no network collisions occur; (ii) convergence to a prescribed local set around the origin is guaranteed for all plants. When formulating an algorithm, we additionally propose an optimization problem that is similar to the standard collision avoidance problem of controlling multi-agent systems. To validate our proposed scheme, a control problem of three inverted pendulums is simulated. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.