A probabilistic approach for control of a stochastic system from LTL specifications
A probabilistic approach for control of a stochastic system from LTL specifications
复制标题
根据 LTL 规范控制随机系统的概率方法
DOI：
--
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
C. Belta
中科院分区：
文献类型：
--
作者：
Morteza Lahijanian;S. Andersson;C. Belta
我们考虑控制一个连续时间线性随机系统的问题，从一个线性时序逻辑（LTL）公式在一组线性谓词的系统状态的规格。我们提出了一个三步解决方案。首先，我们定义了一个多面体分区的状态空间和控制器的有限集合，表示为符号，并构造一个马尔可夫决策过程（MDP）。其次，通过使用类似LTL模型检测的算法，我们确定一个运行满足相应的Kripke结构中的公式。第三，我们确定了一个序列的控制动作的MDP，最大限度地提高以下的概率令人满意的运行。我们提出说明性的模拟结果。
We consider the problem of controlling a continuous-time linear stochastic system from a specification given as a Linear Temporal Logic (LTL) formula over a set of linear predicates in the state of the system. We propose a three-step solution. First, we define a polyhedral partition of the state space and a finite collection of controllers, represented as symbols, and construct a Markov Decision Process (MDP). Second, by using an algorithm resembling LTL model checking, we determine a run satisfying the formula in the corresponding Kripke structure. Third, we determine a sequence of control actions in the MDP that maximizes the probability of following the satisfying run. We present illustrative simulation results.