Verifying Stochastic Hybrid Systems with Temporal Logic Specifications via Model Reduction

Yu Wang, Nima Roohi, Matthew West, Mahesh Viswanathan, G. Dullerud
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引用次数: 1

Abstract

We present a scalable methodology to verify stochastic hybrid systems for inequality linear temporal logic (iLTL) or inequality metric interval temporal logic (iMITL). Using the Mori–Zwanzig reduction method, we construct a finite-state Markov chain reduction of a given stochastic hybrid system and prove that this reduced Markov chain is approximately equivalent to the original system in a distributional sense. Approximate equivalence of the stochastic hybrid system and its Markov chain reduction means that analyzing the Markov chain with respect to a suitably strengthened property allows us to conclude whether the original stochastic hybrid system meets its temporal logic specifications. Based on this, we propose the first statistical model checking algorithms to verify stochastic hybrid systems against correctness properties, expressed in iLTL or iMITL. The scalability of the proposed algorithms is demonstrated by a case study.
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用模型约简验证具有时间逻辑规范的随机混合系统
我们提出了一种可扩展的方法来验证不等式线性时间逻辑(iLTL)或不等式度量间隔时间逻辑(iMITL)的随机混合系统。利用Mori-Zwanzig约简方法,构造了给定随机混合系统的有限状态马尔可夫链约简,并证明了该约简马尔可夫链在分布意义上近似等价于原系统。随机混合系统及其马尔可夫链约简的近似等价性意味着对马尔可夫链的适当强化性质进行分析,可以得出原始随机混合系统是否满足其时间逻辑规范。在此基础上,我们提出了第一个统计模型检查算法来验证随机混合系统的正确性,以iLTL或iMITL表示。通过实例分析验证了所提算法的可扩展性。
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