Output Feedback Model Predictive Control for NCSs with Input Quantization

This paper addresses the robust output feedback model predictive control (MPC) schemes for networked systems (NCSs) with input quantization. The logarithmic quantizer is considered in this paper, and sector bound approach applied, which appropriately treats quantization error as a sector-bounded uncertainty. presented method involves an offline designed state observer using linear matrix inequality (LMI) online MPC algorithms optimize one free move followed by estimated state. Moreover, due to uncertainty of estimation error, technique refreshing provided so guarantee recursive feasibility optimization problem. proposed inherit characteristics synthesis MPC, guaranteeing problem stability closed-loop system, explicitly account error. Two simulation examples are given illustrate effectiveness methods.