JOURNAL ARTICLE

MixedH2/Hdistributed robust model predictive control for polytopic uncertain systems subject to actuator saturation and missing measurements

Yan SongXiaosheng FangQingda Diao

Year: 2014 Journal:   International Journal of Systems Science Vol: 47 (4)Pages: 777-790   Publisher: Taylor & Francis

Abstract

In this paper, we discuss the mixed H2/H∞ distributed robust model predictive control problem for polytopic uncertain systems subject to randomly occurring actuator saturation and packet loss. The global system is decomposed into several subsystems, and all the subsystems are connected by a fixed topology network, which is the definition for the packet loss among the subsystems. To better use the successfully transmitted information via Internet, both the phenomena of actuator saturation and packet loss resulting from the limitation of the communication bandwidth are taken into consideration. A novel distributed controller model is established to account for the actuator saturation and packet loss in a unified representation by using two sets of Bernoulli distributed white sequences with known conditional probabilities. With the nonlinear feedback control law represented by the convex hull of a group of linear feedback laws, the distributed controllers for subsystems are obtained by solving an linear matrix inequality (LMI) optimisation problem. Finally, numerical studies demonstrate the effectiveness of the proposed techniques.

Keywords:
Control theory (sociology) Actuator Convex hull Network packet Bernoulli's principle Linear matrix inequality Packet loss Model predictive control Nonlinear system Distributed parameter system Mathematics Computer science Mathematical optimization Regular polygon Engineering Control (management) Differential equation

Metrics

21
Cited By
3.11
FWCI (Field Weighted Citation Impact)
28
Refs
0.93
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Stability and Control of Uncertain Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Advanced Control Systems Optimization
Physical Sciences →  Engineering →  Control and Systems Engineering
Distributed Control Multi-Agent Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications

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