LAUSR

In this article, we consider the design of dynamic transmission scheduling policies for the industrial network systems sharing scarce communication resources. Only a few subsystems can obtain channel access for information updates to close their control loops at each time step, which highlights the necessity of designing optimal transmission scheduling schemes to achieve a minimum average linear quadratic cost of the industrial network systems. We first propose a greedy state-error-dependent scheduling (SES) policy based on the one-step expected profit and discuss its stability employing the Lyapunov function method. After formulating the scheduling optimization as a Markov decision process problem and relaxing with a soft constraint, we develop a heuristic near-optimal solution that guarantees the optimality of certainty equivalent controllers, namely, Whittle’s index-inspired error-dependent scheduling (WIES). A stochastic stability condition of WIES is further given based on f-ergodicity. Due to low computational complexity and ease of implementation, the proposed schemes are suitable for large-scale heterogeneous industrial network systems. Finally, simulation results show that the proposed policies outperform the existing round-robin, holding-time-prioritized, and error-aware scheduling schemes.