论文标题
连续时间随机混合系统的控制屏障功能的组成构建
Compositional Construction of Control Barrier Functions for Continuous-Time Stochastic Hybrid Systems
论文作者
论文摘要
在这项工作中,我们提出了一个组成框架,用于构建连续时间随机混合系统网络的控制屏障功能,从而实施有限状态自动机表示的复杂逻辑规格。所提出的方案是基于用于子系统计算的所谓伪轰炸机函数的概念,它可以采用该函数,该函数可以通过有限时间的地平线上的互连系统合成混合控制器来合成混合控制器。特别是,我们首先利用足够的小增益类型条件来基于基于针对子系统计算的相应伪轰炸函数的互连系统的组成壁垒函数。然后,使用构造的控制屏障函数,我们就可以满足给定的复杂规格在有限的时间范围内提供概率保证。在这方面,我们根据代表原始有限状态自动机的补充的自动机将给定的复杂规范分解为更简单的可及性任务。然后,我们提供系统的方法来通过计算相应的伪式栏功能来解决这些简单的可及性任务。根据(i)基于(SOS)优化程序和(ii)反示例引导的归纳合成(CEGIS)提供两种不同的系统技术,以搜索子系统的伪栏功能,同时合成本地控制器。我们通过将它们应用于具有马尔可夫开关信号的100个非线性振荡器的完全连接的库拉莫托网络,以证明我们提出的结果的有效性。
In this work, we propose a compositional framework for the construction of control barrier functions for networks of continuous-time stochastic hybrid systems enforcing complex logic specifications expressed by finite-state automata. The proposed scheme is based on a notion of so-called pseudo-barrier functions computed for subsystems, by employing which one can synthesize hybrid controllers for interconnected systems enforcing complex specifications over a finite-time horizon. Particularly, we first leverage sufficient small-gain type conditions to compositionally construct control barrier functions for interconnected systems based on the corresponding pseudo-barrier functions computed for subsystems. Then, using the constructed control barrier functions, we provide probabilistic guarantees on the satisfaction of given complex specifications in a bounded time horizon. In this respect, we decompose the given complex specification to simpler reachability tasks based on automata representing the complements of original finite-state automata. We then provide systematic approaches to solve those simpler reachability tasks by computing corresponding pseudo-barrier functions. Two different systematic techniques are provided based on (i) the sum-of-squares (SOS) optimization program and (ii) counter-example guided inductive synthesis (CEGIS) to search for pseudo-barrier functions of subsystems while synthesizing local controllers. We demonstrate the effectiveness of our proposed results by applying them to a fully-interconnected Kuramoto network of 100 nonlinear oscillators with Markovian switching signals.