Stability Analysis of Nonlinear Networked Control Systems Using Model Predictive Control Scheme

Abstract

Model predictive control (MPC) has received much attention in the past decades due to its extensive applications in the control of industrial processes such as distillation and fractionation, pulp and paper processing. It works on the principle of receding horizon control, where only the first change in each independent variable u(k|k) is implemented, and the calculation is repeated when the next change is required. This feature makes the MPC approach very appropriate to incorporate the input/output constraints into the on-line optimization as well as to compensate time delays, which increases the possibility of its application in the synthesis and analysis of Networked Control Systems (NCS). In this work, an observer based MPC will be applied to Nonlinear Networked Control Systems (NNCS). Due to space limit, the NNCS problem is formulated first, then only the theory of stability is developed and reported. In the next work, the controller and the observer gains will be established. The results will be tested with simulation.