K-means based delay quantization and prediction in networked control systems

In the networked control system (NCS) with the discrete-time hidden Markov model (DTHMM), K-means clustering is proposed in this paper to quantize the controller-to-actuator (C-A) delays and to obtain the discrete observations for estimating the DTHMM parameters. The prediction of the current stochastic C-A delay is achieved based on the quantizing method and the estimated DTHMM. Then, by taking the current predicted C-A delay into account, a state-feedback controller is designed to directly compensate for the effect of the current real C-A delay on the NCS. The detailed procedure of the K-means clustering used to quantize the past C-A delays is given. The contrastive simulation experiments are implemented, and the results demonstrate the superiority of the quantizing and predictive methods proposed in this paper.