Transmission Scheduling in Wireless Networked Control for Industrial IoT

Wireless networked control systems (WNCS) consist of spatially distributed sensors, actuators, and controllers communicating through wireless networks. WNCS has recently emerged as a fundamental infrastructure technology to enable reliable control for mission-critical Industrial Internet of Things (IIoT) applications such as factory automation, intelligent transportation systems, telemedicine and smart grids. The design of WNCS requires the joint design of communications, computing and control. WNCS faces challenges such as unreliable transmission and latency in transmitting control and sensing information due to channel impairment in wireless communications for large scale deployment. This can have a significant impact on the stability and performance of WNCS. Most existing works have mainly focused on the design of WNCS from a control perspective rather than communications or have considered an ideal or simplified wireless model. How to reliably control WNCS in practical wireless channels and design wireless communication scheduling policy to optimize control performance is a challenging task. This thesis presents the design of practical communication protocols of a general discrete linear time-invariant (LTI) dynamic system in WNCS. We address the transmission scheduling problems in WNCS in three scenarios, which require the development of different strategies. Firstly, to minimize the long-term average remote estimation mean-squared-error (MSE), a hybrid automatic repeat request (HAQR)-based real-time estimation framework is proposed. Secondly, a downlink-uplink transmission scheduling policy is developed for a half-duplex (FD) controller to optimize the system performance. Finally, a novel controller with adaptive packet length is studied, and a variable-length packet-transmission policy is proposed to balance the delay-reliability tradeoff in WNCS optimally. Numerical results show that our dynamic scheduling policies can significantly improve the performance of WNCS in terms of estimation and control costs while maintaining the stability of the system