论文标题
基于STL的网络物理系统弹性控制方法
An STL-based Approach to Resilient Control for Cyber-Physical Systems
论文作者
论文摘要
我们提出了弹性，这是对符合基于STL的要求的网络物理系统弹性控制的框架。弹性利用最近开发的形式主义来指定$（\ Mathit {rec}，\ Mathit {dur}）$ real-partaured Pairs的集合，其中$ \ Mathit {Rec} $代表该系统从系统中快速恢复的能力（可恢复的能力），并且是$ \ Mathit的能力（dur}） （耐用性）。我们将弹性STL控制问题定义为多目标优化之一，其中最大化所需的STL规范的可恢复性和耐用性。当两项目标都优先于另一个目标时，解决问题的方法是一组帕累托最佳的系统轨迹。我们使用混合刻板线性编程编码和A Posteriori $ε$ -Sonstraint方法提出了一种精确的解决方案方法，以有效地检索完整的最佳弹性解决方案集。在每个时间步骤中，通过决策者策略从帕累托最佳解决方案中选择的最佳控制动作实现了模型预测控制的形式。我们在两个重要的案例研究中证明了弹性框架的实际实用性：自动驾驶汽车车道保存和截止日期驱动的多区域套餐。
We present ResilienC, a framework for resilient control of Cyber-Physical Systems subject to STL-based requirements. ResilienC utilizes a recently developed formalism for specifying CPS resiliency in terms of sets of $(\mathit{rec},\mathit{dur})$ real-valued pairs, where $\mathit{rec}$ represents the system's capability to rapidly recover from a property violation (recoverability), and $\mathit{dur}$ is reflective of its ability to avoid violations post-recovery (durability). We define the resilient STL control problem as one of multi-objective optimization, where the recoverability and durability of the desired STL specification are maximized. When neither objective is prioritized over the other, the solution to the problem is a set of Pareto-optimal system trajectories. We present a precise solution method to the resilient STL control problem using a mixed-integer linear programming encoding and an a posteriori $ε$-constraint approach for efficiently retrieving the complete set of optimally resilient solutions. In ResilienC, at each time-step, the optimal control action selected from the set of Pareto-optimal solutions by a Decision Maker strategy realizes a form of Model Predictive Control. We demonstrate the practical utility of the ResilienC framework on two significant case studies: autonomous vehicle lane keeping and deadline-driven, multi-region package delivery.
