State-to-Noise-Ratio Based Transmission Scheduling in Wireless Control Systems for IIoT

In industrial internet-of-things (IIoT), conventional event-triggered control method requires sensors continuously monitoring control states in periodical time. This would consume a huge amount of energy resource, which impedes the application of such conventional methods since the sensors are powered by batteries in most cases. To deal with this issue, this paper proposes a new state-to-noise-ratio (SNR) based transmission scheduling method from wireless communication perspective. Specifically, we first adopt an Additive White Gaussian Noise (AWGN) channel model to represent the event-triggered control model, by which we can convert the original event-triggered control problem into a wireless transmission scheduling problem from the sensor to the controller. Based on that, the mutual information is proposed to measure the value of the control states. More importantly, a new control SNR is defined based on mutual information. Using control SNR as the transmission activating criterion, perfect state observation assumption and sensor’s monitoring with periodical time in traditional event-triggered control are no longer needed. Furthermore, we provide an analytical expression of dynamic SNR thresholds to determine whether the transmission should be activated. Finally, we prove the mean-square stability of our proposed method. Numerical comparisons are provided to demonstrate the effectiveness of our proposed method.