A synthesis approach to predictive control for networked control systems

Author

Yuanyuan Zou ; James, Lam ; Yugang Niu ; Dewei Li

Author_Institution

Key Lab. of Adv. Control & Optimization for Chem. Process, East China Univ. of Sci. & Technol., Shanghai, China

fYear

2014

fDate

28-30 July 2014

Firstpage

7715

Lastpage

7720

Abstract

This paper studies a synthesis approach to predictive control for networked control systems with data loss and quantization. An augmented Markov jump linear model with polytopic uncertainties is modeled to describe the quantization errors and possible data loss. Based on this model, a predictive control synthesis approach is developed, which involves online optimization of a infinite horizon objective and conditions to deal with system constraints. The proposed MPC algorithm guarantees closed-loop mean-square stability and constraints satisfaction.

Keywords

Markov processes; control system synthesis; linear systems; networked control systems; optimisation; predictive control; quantisation (signal); stochastic systems; MPC algorithm; augmented Markov jump linear model; closed-loop mean-square stability; constraint satisfaction; data loss; infinite horizon objective; networked control systems; online optimization; polytopic uncertainties; predictive control synthesis approach; quantization errors; system constraints; Data models; Educational institutions; Networked control systems; Predictive control; Quantization (signal); Symmetric matrices; Networked Control Systems; Predictive Control; Stabilit;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2014 33rd Chinese

Conference_Location

Nanjing

Type

conf

DOI

10.1109/ChiCC.2014.6896286

Filename

6896286