scholarly journals Optimal Control for Networked Control Systems with Markovian Packet Losses

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiao Han ◽  
Zhijian Ji ◽  
Qingyuan Qi

This paper is concerned with the optimal output feedback control problem for networked control systems (NCSs) with Markovian packet losses. In this paper, the packet losses occur both between the sensor and controller and between the controller and actuator. Moreover, the packet loss channels are described with two-state Markov chains. Since the precise state information cannot be obtained, thus an optimal recursive estimator is designed. Furthermore, by adopting the dynamic programming approach, we derive the optimal output feedback control, which is based on the solution to a given modified Riccati equation. The obtained results can be seen as an important implementation of the control theory for NCSs with unreliable communication channels.

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 779 ◽  
Author(s):  
Wookyong Kwon ◽  
Jaemin Baek

Networked control systems are widely spread, which is composed of numerous sensor and control nodes through communication channel. In this paper, an event-triggered H ∞ memory output feedback control (EMOFC) is investigated for networked control linear systems in discrete form. The memory control employing memorized past information is exploited to enhance the triggering intervals under event-triggered condition. Moreover, novel summation type event-triggering condition is newly proposed by utilizing buffer memory element. Based upon memory control and novel triggering conditions, the control design methodology is constructed for transformed input-delay model in forms of linear matrix inequalities (LMIs) adopting generalized free-weighting matrix summation inequality. As a result, the proposed scheme shows off the reduction of average signal transmission frequency and reliability while covering standard condition. Throughout numerical examples, the effectiveness is shown and the effect of memory element is analyzed.


2014 ◽  
Vol 61 (1) ◽  
pp. 512-520 ◽  
Author(s):  
Rongni Yang ◽  
Guo-Ping Liu ◽  
Peng Shi ◽  
Clive Thomas ◽  
Michael V. Basin

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