Model predictive control of non-linear systems over networks with data quantization and packet loss

- We establish a novel T-S fuzzy model for nonlinear NCS with packet losses and data quantizations in both communication links.
- A fuzzy model predictive controller is properly designed to guarantee the closed-loop stability.
- The closed-loop system stochastically stable in the mean square has been studied and the recursive feasibility of the optimiatzation problem is investigated.

This paper studies the approach of model predictive control (MPC) for the non-linear systems under networked environment where both data quantization and packet loss may occur. The non-linear controlled plant in the networked control system (NCS) is represented by a Tagaki-Sugeno (T-S) model. The sensed data and control signal are quantized in both links and described as sector bound uncertainties by applying sector bound approach. Then, the quantized data are transmitted in the communication networks and may suffer from the effect of packet losses, which are modeled as Bernoulli process. A fuzzy predictive controller which guarantees the stability of the closed-loop system is obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method.