As messages and nodes over a network increase, delay time in a networked control system (NCS) increases and results in frequent dropout, thereby seriously degrading the performance and stability of NCS. Therefore, effective methods are urgently needed to handle the time delay and dropout effects of NCS. In this paper, a real-time transition probability estimator for the two-state Markov chain model is proposed for online monitoring of the dropout condition by using a short-window technique. Furthermore, under time-varied dropout conditions, the most suitable least-square estimator can be determined in real time by applying intelligent message estimator (IME), and missing data from NCS can be efficiently estimated and restored.
|Name|| IEEE International Conference on Systems Man and Cybernetics Conference Proceedings|
|Conference||2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014|
|Period||5/10/14 → 8/10/14|