Qualitative modelling of continuous-variable systems by means of non deterministic automata

J. Lunze
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引用次数: 15

Abstract

Considers the problem of qualitative modelling of discrete-time continuous-variable dynamical systems, for which only a quantised measurement (x(k)) of the state x(k) is available. The qualitative model has to describe the qualitative trajectory x(1), x(2),. . . for given qualitative initial state x(0) and qualitative input sequence. First, it is shown that the qualitative trajectory of the system is ambiguous. Hence, the qualitative model has to be nondeterministic. Secondly, it is shown that nondeterministic automata provide reasonable qualitative models of the continuous-variable system. The relation between the automaton and the given system shows what knowledge about the system has to be available if the qualitative model is to be set up. Thirdly, the authors propose to use stochastic automata, which provide a means for weighting each state concerning its appearance on the qualitative trajectory of the continuous-variable system. On this basis, the set of spurious solutions, which exist for any qualitative model, can be reduced. The suitability of the model becomes obvious by designing a qualitative controller. The results are illustrated by the problem of stabilising an 'inverted pendulum'. >
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用不确定自动机对连续变量系统进行定性建模
考虑了离散时间连续变量动力系统的定性建模问题,其中只有状态x(k)的量化测量(x(k))可用。定性模型必须描述定性轨迹x(1), x(2),…对于给定的定性初始状态x(0)和定性输入序列。首先,系统的定性轨迹是模糊的。因此,定性模型必须是不确定的。其次,证明了不确定性自动机为连续变量系统提供了合理的定性模型。自动机和给定系统之间的关系表明,如果要建立定性模型,必须获得关于系统的哪些知识。第三,作者提出使用随机自动机,它提供了一种方法来加权每个状态的出现在定性轨迹上的连续变量系统。在此基础上,可以简化任意定性模型存在的伪解集。通过设计一个定性控制器,模型的适用性变得明显。结果通过稳定一个“倒立摆”的问题来说明。>
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