Abstract:
Expert control systems emulate the decision making ability of a human expert for solving complex problems by reasoning about knowledge. Artificial intelligence techniques are usually used for the purpose of representing
knowledge and for generating control decisions through an appropriate reasoning mechanism. In this paper, the generalized form of knowledge representation
models in expert control systems is represented. Furthermore, an algorithm for
deriving managerial decisions based on the method of resolving is described.
Unified control models are proposed that allow one to determine combinations
of control operations that can bring the control object to normal if it goes beyond the permissible ranges of several characteristics. It is proved that when assessing the characteristics of the state of the control object in qualitative categories, the task of deriving a managerial decision is reduced to solving a system of
linear equations with Boolean variables or combinatorial optimization problems. Algorithms for solving such problems that implement the idea of a directed enumeration of options are indicated.
