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Probabilistic-constrained optimal control of a class of stochastic hybrid systems

机译:一类随机混合系统的概率约束最优控制

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摘要

Stochastic hybrid systems have several applications such as biological systems and communication networks, but it is difficult to consider control of general stochastic hybrid systems. In this paper, a class of discrete-time stochastic hybrid systems, in which only discrete dynamics are stochastic, is considered. For this system, a solution method for the optimal control problem with probabilistic constraints is proposed. Probabilistic constraints guarantee that the probability that the continuous state reaches a given unsafe region is less than a given constant. In the propose method, first, continuous state regions, from which the state reaches a given unsafe region, are computed by a backward-reachability graph. Next, mixed integer quadratic programming problems with constraints derived from the backward-reachability graph are solved. The proposed method can be applied to model predictive control.
机译:随机混合系统具有多种应用,例如生物系统和通信网络,但是很难考虑控制一般的随机混合系统。在本文中,考虑了一类离散时间随机混合系统,其中仅离散动态是随机的。针对该系统,提出了一种具有概率约束的最优控制问题的求解方法。概率约束保证了连续状态到达给定不安全区域的概率小于给定常数。在提出的方法中,首先,通过后向可达性图来计算状态从该连续状态区域到达给定的不安全区域。接下来,解决具有从后向可达性图导出的约束的混合整数二次规划问题。所提出的方法可以应用于模型预测控制。

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