Control Vector Selection for Extended Packetized Predictive Control in Wireless Networked Control Systems

Keisuke NAKASHIMA  Takahiro MATSUDA  Masaaki NAGAHARA  Tetsuya TAKINE  

IEICE TRANSACTIONS on Communications   Vol.E103-B   No.7   pp.748-758
Publication Date: 2020/07/01
Publicized: 2020/01/15
Online ISSN: 1745-1345
DOI: 10.1587/transcom.2019EBP3209
Type of Manuscript: PAPER
Category: Network
wireless networked control systems,  extended packetized predictive control,  bursty packet losses,  random delays,  control vector selection,  

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We study wireless networked control systems (WNCSs), where controllers (CLs), controlled objects (COs), and other devices are connected through wireless networks. In WNCSs, COs can become unstable due to bursty packet losses and random delays on wireless networks. To reduce these network-induced effects, we utilize the packetized predictive control (PPC) method, where future control vectors to compensate bursty packet losses are generated in the receiving horizon manner, and they are packed into packets and transferred to a CO unit. In this paper, we extend the PPC method so as to compensate random delays as well as bursty packet losses. In the extended PPC method, generating many control vectors improves the robustness against both problems while it increases traffic on wireless networks. Therefore, we consider control vector selection to improve the robustness effectively under the constraint of single packet transmission. We first reconsider the input strategy of control vectors received by COs and propose a control vector selection scheme suitable for the strategy. In our selection scheme, control vectors are selected based on the estimated average and variance of round-trip delays. Moreover, we solve the problem that the CL may misconceive the CO's state due to insufficient information for state estimation. Simulation results show that our selection scheme achieves the higher robustness against both bursty packet losses and delays in terms of the 2-norm of the CO's state.