Quantitative Analysis for Networked Output Feedback MPC of Clock Synchronization in Unreliable WSN

Abstract

In the industrial cyber-physical environment, the performance of clock synchronization with loss of data packets should be analyzed quantitatively. The localized state estimator and controller are designed to realize the speed of convergence for exponential stability of the clock synchronization for the output feedback tubes-model predictive control (Tubes-MPC) of the state-space model. The upper and lower bounds for the variance of synchronization error under the statistical significance were quantitatively analyzed in incomplete measurement. The set of interference error in complete measurement was added into the set of additional estimated errors introduced by packet loss. Clock synchronization of the output feedback Tubes-MPC which has been constructed still has the performance of robust exponential convergence under networked packet loss, and it can be extended to an absolute state-space model with network-level in a unified approach.

ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things

“…It is a parameter estimation method using the expectation maximization (EM) algorithm based on Kalman filtering. For unreliable wireless link communication, Ting Wang et al, (2019) established a Tubes-MPC [ 13 ] clock synchronization method that is based on the predictive control method with the output feedback model, the stable quantitative convergence performance of the clock synchronization index is achieved. The model prediction optimization model is established under the set of constraints, and the quantitative convergence performance of the stability of robust packet loss synchronization index under the clock is achieved.…”

“…When considering the loss of observation, it is necessary to adjust the parameter of the Kalman filtering model. By analyzing the iterative process of error covariance, the relationship between the convergence of packet reception rate and covariance matrix expectation is discussed [ 13 ].…”

“…On the other hand, due to the existence of various random noises in the calculation and measurement of clock offset and skew, outliers [ 13 , 15 , 16 ] may exist in the filtered system state, which seriously reduces the reliability of data. However, the Kalman filtering algorithm is highly dependent on data, which is easily influenced by outliers and affect the filter accuracy.…”

“…Additionally, a novel adaptive robust synchronization (ABS) framework based on Kalman filter is designed to determine the sampling period to achieve the customized accuracy. The design of this paper is to analyze [ 13 ] the upper and lower bounds of error variance with the unreliable link clock by Kalman filter, and introduce the uncertainty driving mechanism to adjust the synchronous sampling period of clock adaptively. This is not the traditional periodic synchronization, but the communication overhead is minimized when the clock accuracy is reached.…”