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A Partial Order Approach to Discrete Dynamic Feedback in a Class of Hybrid Systems

机译:一类混合系统离散动态反馈的偏序方法

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We consider the dynamic feedback problem in a class of hybrid systems modeled as (infinite) state deterministic transition systems, in which the continuous variables are available for measurement. The contribution of the present paper is twofold. First, a novel framework for performing dynamic feedback is proposed which relies on partial orders on the sets of inputs and of discrete states. Within this framework, a state estimator updates a lower and an upper bound of the set of current states. A controller then uses such upper and lower bounds to compute the upper and lower bounds of the set of inputs that maintain the current state in a desired set. Second, we show that under dynamic controllability assumptions, the conditions that allow to apply the developed algorithms can always be verified. Therefore, the partial order approach to dynamic feedback is general. A multi-robot system is presented to show the computational advantages in a system in which the size of the state set can be so large as to render enumeration and exhaustive techniques inapplicable.
机译:我们在建模为(无限)状态确定性过渡系统的一类混合系统中考虑动态反馈问题,其中连续变量可用于测量。本文的贡献是双重的。首先,提出了一种用于执行动态反馈的新颖框架,该框架依赖于输入集和离散状态的部分顺序。在此框架内,状态估计器会更新当前状态集的下限和上限。控制器然后使用这种上限和下限来计算将当前状态保持在所需集中的一组输入的上限和下限。其次,我们表明在动态可控性假设下,可以始终验证允许应用已开发算法的条件。因此,动态反馈的偏序方法是通用的。提出了一种多机器人系统,以显示系统中的计算优势,在该系统中,状态集的大小可能太大,以致于枚举和穷举技术不适用。

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