Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems

    •  Ma, Y., Guo, J., Wang, Y., Chakrabarty, A., Ahn, H., Orlik, P.V., Guan, X., Lu, C., "Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems", IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, DOI: 10.1109/​TCST.2022.3141581, May 2022.
      BibTeX TR2022-043 PDF
      • @article{Ma2022may,
      • author = {Ma, Yehan and Guo, Jianlin and Wang, Yebin and Chakrabarty, Ankush and Ahn, Heejin and Orlik, Philip V. and Guan, Xinping and Lu, Chenyang},
      • title = {Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems},
      • year = 2022,
      • month = may,
      • doi = {10.1109/TCST.2022.3141581},
      • url = {}
      • }
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  • Research Areas:

    Communications, Control, Optimization, Signal Processing


Wireless networked control systems (WNCS) have the potential to revolutionize industrial automation in smart factories. Optimizing closed-loop performance while maintaining stability is a fundamental challenge in WNCS due to limited bandwidth and non-deterministic link quality of wireless networks. In order to bridge the gap between network design and control system performance, we propose an optimal dynamic transmission scheduling strategy that optimizes performance of multi-loop control systems by allocating network resources based on predictions of both link quality and control performance at run-time. We formulate the optimal dynamic scheduling problem as a nonlinear integer programming problem, which is relaxed to a linear programming problem. We further extend the optimization problem to balance control performance and communication cost. The proposed optimal dynamic scheduling strategy renders the closed-loop system mean-square stable under mild assumptions. Its efficacy is demonstrated by simulating a four-loop control system over an IEEE 802.15.4 wireless network simulator – TOSSIM. The run-time network reconfiguration protocol tailored for optimal scheduling is designed and implemented on a real wireless network consisting of IEEE 802.15.4 devices. Hybrid simulations integrating a real wireless network and simulated physical plant control are performed. Simulation and experimental results show that the optimal dynamic scheduling can enhance control system performance and adapt to both constant and variable wireless interference and physical disturbance to the plant.


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