By Professor Zdzislaw Bubnicki PhD (auth.)
A unified and systematic description of research and selection difficulties inside of a large classification of doubtful platforms, defined by means of conventional mathematical tools and via relational wisdom representations.
With exact emphasis on doubtful keep an eye on structures, Professor Bubnicki delivers a distinct method of formal versions and layout (including stabilization) of doubtful structures, according to doubtful variables and similar descriptions.
• advent and improvement of unique thoughts of doubtful variables and a studying technique including wisdom validation and updating.
• Examples about the keep watch over of producing structures, meeting procedures and activity distributions in computers point out the chances of functional purposes and techniques to determination making in doubtful systems.
• contains specific difficulties similar to attractiveness and regulate of operations below uncertainty.
If you have an interest in difficulties of doubtful keep watch over and determination help structures, it will be a beneficial addition on your bookshelf. Written for researchers and scholars within the box of regulate and knowledge technological know-how, this booklet also will gain designers of data and keep an eye on systems.
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Extra resources for Analysis and Decision Making in Uncertain Systems
4 Determinization The deterministic decision algorithm based on the knowledge KD may be obtained as a result of determinization (see Sect. P(z). P(z). For the given desirable value y * we can consider two cases: in the first case the deterministic decision algorithm IJ'(z) is obtained via determinization of the knowledge of the plant KP, and in the second case the deterministic decision algorithm IJ'd(z) is based on the determinization of the knowledge of the decision making KD obtained from KP for the given y • .
For the plant with external disturbances z described by a function y = , u and z find the probability density fy(Y Iu,z) -1 x =
and / (a desirable output) are given. Decision problem: Version I. To find the decision u ~ u0 maximizing /y(/; u,z) ~ In the first and the third description, z is assumed to be a value of a random variable z. In the parametric case we have the function y = and u find the probability density fy(Y lu) ~ fy(y;u) of the random variable y =
In the first and the third description, z is assumed to be a value of a random variable z. In the parametric case we have the function y =
and u find the probability density fy(Y lu) ~ fy(y;u) of the random variable y =