Priority-based scheduling strategies are often used to resolve contentions in resource constrained control systems. Such scheduling strategies inevitably introduce time delays into controls and may degrade the performance of control systems. Considering the coupling between priority assignment and control, this paper presents a method to co-design priority assignments and control laws for each control system, which aims to minimize the overall performance degradation caused by contentions. The co-design problem is formulated as a mixed integer optimization problem with a very large search space, rendering difficulty in computing the optimal solution. To solve the problem, we develop a novel contention-resolving model predictive control method to dynamically assign priorities and compute an optimal control. The priority assignment can be determined using a sample-based approach without excessive demand on computing resources, and optimal controls can be computed iteratively following the order of the assigned priorities. We apply the proposed contention-resolving model predictive control to co-design scheduling and controls in networked control systems. We present simulation results to show the effectiveness of our proposed method.

基于优先级的调度策略通常用于解决资源受限控制系统中的争用。这样的调度策略不可避免地在控制中引入时间延迟，并且可能降低控制系统的性能。考虑到优先级分配和控制之间的耦合，本文提出了一种共同设计每个控制系统的优先级分配和控制律的方法，旨在最大程度地减少竞争引起的整体性能下降。协同设计问题被公式化为具有很大搜索空间的混合整数优化问题，这给计算最优解带来了困难。为了解决该问题，我们开发了一种新颖的竞争解决模型预测控制方法，可以动态分配优先级并计算最佳控制。可以使用基于样本的方法来确定优先级分配，而无需过多的计算资源需求，并且可以按照分配的优先级的顺序迭代地计算最佳控件。我们将提出的竞争解决模型预测控制应用于网络控制系统中的协同设计调度和控制。我们目前的仿真结果表明了我们提出的方法的有效性。