M.G. Semenenko - Ph.D. (Phys.-Math.), Associate Professor, All-Russian State Distance-Learning Institute of Finance and Economics, Kaluga branch. E-mail: msemenenko09@rambler.ru

An incompleteness and illegibility of the information both the insufficient reliability and degree of formalisation of the initial data are characteristic for many control systems of difficult technological processes and objects. For work with such objects the formalism of Fuzzy Logic is often used last decades in which basis the concept of fuzzy set lies. In the theory of sets usual («unfuzzy») set A is considered as a part of some universal set U. For example, U is a set of all battery types and A is a set of lead-acid batteries. In this case it is possible to say about each element of the universal set unequivocally whether it belongs to set A. If we enter a concept of an element membership function to the set A it will accept two values: 1 (if the element belongs to set A) and 0 otherwise. According to the concept of Professor of University of Berkeley in California Lotfi Zadeh a membership function can accept any values on a segment of [0; 1] for some types of objects. In this case the value of membership function characterizes a probability an element belongs to set A. Further in L. Zade's and his followers works the concepts of operations on fuzzy sets, fuzzy logic conclusion and the concept of a linguistic variable have been entered. There was a concept of fuzzy control in engineering practice when difficult technical object control occurs in the conditions of the incomplete and-or not enough formalized information. The similar approach is used both in modelling of difficult technical objects and for creation of real devices of automatic control by similar objects. Speaking about the fuzzy logic they frequently mean the systems of an fuzzy conclusion which underlie various expert and control systems. The formation of rule database (knowledge base) of fuzzy conclusion system is a stage of fuzzy conclusion in which basis the rules of «if-then» type lie. The output variable membership function is under construction on the basis of these rules, for example, on the basis of Mamdani algorithm, and a strict value of an output variable turns out. In the present work application of fuzzy logic methods to two types of objects is considered: management of the battery (accumulator) charging device and an estimation of the investment efficiency into high technologies. Both output variables and their membership functions are defined for each object, the knowledge base is generated and calculations for typical values of input variables are carried out.