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本文通过引入马氏决策过程中的迭代算法,研究了计时离散事件系统的随机优化监控综合问题。为了对不确定的人造系统实施监控,在考虑事件的操作时间的基础上,利用带有发生事件概率分布函数的随机计时离散事件系统模型对系统建模。为了对这类随机系统实施监控,在传统方法中,采用控制任务的最大可控子语言设计控制器,不能体现系统模型的随机特性。本文提出利用软控制任务代替原控制任务的方法,使其超出原控制任务的概率在给定的容许度约束范围内。首先,通过在计时离散事件系统中定义计时事件的发生概率映射和发生费用函数,利用离散事件系统的逻辑特性,构造事件发生序列的期望费用函数,进而确立马氏决策过程的最优方程,建立软控制任务与期望费用函数之间的关系。然后,通过计算事件发生序列的费用值,提出利用有限费用值可以用来确定软控制任务,进而基于逻辑监控方法,确定最优监控器。最后,利用计算有限费用值的迭代过程,提出迭代算法,并给出了计算实例。
In this paper, by introducing the iterative algorithm in the process of Markov decision making, the synthesis optimization problem of time-varying discrete event system is studied. In order to monitor the uncertain man-made system, the system was modeled by using the stochastic chronograph discrete event system model with the event probability distribution function, considering the operating time of the event. In order to monitor such a stochastic system, in the traditional method, the controller with the maximum controllable sub-language of the control task can not reflect the random characteristics of the system model. In this paper, the method of using the soft control task instead of the original control task is proposed to make it exceed the probability of the original control task within the given tolerance. First, by defining the incidence probability function and the cost function of the timing event in the time-discrete event system, the expected cost function of the event sequence is constructed by using the logic characteristics of the discrete event system, and the optimal equation of the decision-making process is established. The relationship between the soft control task and the expected cost function. Then, by calculating the cost of event sequence, it is proposed to use the limited cost value to determine the soft control task, and then to determine the optimal monitor based on the logic monitoring method. Finally, by using the iterative process of calculating the finite cost value, an iterative algorithm is proposed and an example of calculation is given.