The article provides an overview of the levels of development of intelligent systems. The principles of multifactor systems management are examined and illustrated.

Important in the process of managing a multifactor system is the ability to determine the totality of its factors and the interaction of elements. For effective management, it is necessary to understand what changes will entail certain control actions on the system, which means that the management system must "understand" the principles of the operation of the managed system.

Especially it is felt at large industrial and scientific enterprises, where hundreds of subsys-tems – departments and related enterprises are involved in the production process.

In this regard, particular importance is the study and improvement of methods and algorithms for managing multifactor systems and the systematization of this process in modern conditions.

1. Tarasenko F.P. Prikladnoisistemnyianaliz [Applied system analysis]. Moscow, Knorus Publ., 2010. 224 p.

2. Kononov Yu.M. Obzormetodikialgoritmovresheniyazadachupravleniyaproizvodstvennymprotsessomnaosnovepodkhodovsistemnogoanaliza [Review of methods and algorithms for solving the problems of production process managment based on the approaches of system analysis]. SborniknauchnykhtrudovNovosibirskogogosudarstvennogotekhnicheskogouniversiteta – Transaction of scientific papers of the Novosibirsk state technical university, 2017, no. 1 (87),

pр. 72–84.

3. Rubanov V.G., Filatov A.G., Rybin I.A. Intellektual'nyesistemyav-toma-ticheskogoupravleniya. Nechetkoeupravlenie v tekhnicheskikhsistemakh [Intelligent systems of automatic control.Fuzzy control in technical systems]. Available at: http://nrsu.bstu.ru/chap15.html (accessed 29.11.2017).

4. Saridis G.N. Analytical formulation of the principle of increasing precision with decreasing intelligence for intelligent machines. Automatics, 1989, vol. 25, no. 3, pp. 461–467.

5. Zakharov V.N., Ul'yanov S.V. Nechetkiemodeliintellektual'nykh pro-myshlennykhregulyatorovisistemupravleniya: evolyutsiyaiprintsipypostro-eniya[Fuzzy models of intelligent industrial controllers and control systems. Evolution and principles of design].IzvestiyaRossiiskoiakademiinauk.Tekhnicheskayakibernetika – Journal of Computer and Systems Sciences International, 1993, no. 4, pp. 189–205.(In Russian).