Темир йўл транспорти: долзарб масалалар ва инновациялар Ҷилди 1 № 1-2 (2019) · Саҳифаҳои 54-73
SYNTHESIS OF ADAPTIVE NEURO-FUZZY CONTROL SYSTEM OF NONLINEAR DYNAMIC OBJECTS
Сиддиков, Исомиддин, Умурзакова, Дилноза
Аннотатсия
Development of an adaptive neuro-fuzzy control system for nonlinear dynamic objects. Based on the hybrid use of neural networks and fuzzy logic. An application of an adaptive identifier for a neuro-fuzzy control system for a nonlinear dynamic object, functioning in conditions of uncertainty of changes in internal properties and the external environment, is proposed. Algorithms for structural and parametric identification in real time, which is a combination of the algorithm for identifying coefficients of linear equations and the method of the theory of interactive adaptation, have been developed. The structure of the proposed system consists of three parts: the object itself, the controller emulator and the compensator. The developed hybrid model, built on the basis of neural networks and fuzzy models, improves the efficiency of solving the problem of managing complex dynamic objects in conditions of uncertainty. For the formalization of the compensator, the emulator and the regulator, a fuzzy model of Sugeno, the architecture of which consists of five layers, is proposed to be used.
Гибридная модель, модель Сугено, эмулятор, компенсатор, нейро- нечеткая система управления, динамическая объект.Hybrid model, Sugeno model, emulator, compensator, neuro-fuzzy control system, dynamic object
Манбаи метамаълумот: бойгонии OAI-PMH-и маҷалла · Sindex матни пурраро нигоҳ намедорад, ба манбаъ пайванд медиҳад.