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Journal of Applied Mathematics
Volume 2016, Article ID 8249062, 7 pages
http://dx.doi.org/10.1155/2016/8249062
Research Article

Self-Triggered Model Predictive Control for Linear Systems Based on Transmission of Control Input Sequences

Graduate School of Information Science and Technology, Hokkaido University, Sapporo 060-0814, Japan

Received 24 December 2015; Revised 30 March 2016; Accepted 7 April 2016

Academic Editor: Yun-Bo Zhao

Copyright © 2016 Koichi Kobayashi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A networked control system (NCS) is a control system where components such as plants and controllers are connected through communication networks. Self-triggered control is well known as one of the control methods in NCSs and is a control method that for sampled-data control systems both the control input and the aperiodic sampling interval (i.e., the transmission interval) are computed simultaneously. In this paper, a self-triggered model predictive control (MPC) method for discrete-time linear systems with disturbances is proposed. In the conventional MPC method, the first one of the control input sequence obtained by solving the finite-time optimal control problem is sent and applied to the plant. In the proposed method, the first some elements of the control input sequence obtained are sent to the plant, and each element is sequentially applied to the plant. The number of elements is decided according to the effect of disturbances. In other words, transmission intervals can be controlled. Finally, the effectiveness of the proposed method is shown by numerical simulations.