Co-Design of Scalable DMPC and Dynamic Quantizer for Networked Nonlinear Continuous System

This paper presents a co-design control scheme of the scalable Distributed Model Predictive Control and dynamic quantizer for a networked nonlinear system whose topology is reconfigurable, e.g., processing change due to production change and limited networked communication bandwidth. The proposed method, firstly, in each subsystem-based MPC, considers the influence of the dynamic quantizer in the formulation of the optimization problem, which helps better trade off the communication burden and the improvement of the performance of the closed-loop distributed system. Then, the small gain Lyapunov constraint is employed in each subsystem-based optimization problem to keep the stability of the overall system and make the proposed method applicable in a situation where the topology of the system needs to change which increases the scalability of the closed-loop control system. Finally, the simulation results show that the co-design method performs better than the controller where the zoom strategy is set out.