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Neural Network Identifier Design for Dynamic Systems

Student: Viktoriia Iachmeneva

Supervisor: Olga Andrianova

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2020

In this work, dynamic systems with time-varying constraints are studied. The problem of designing the neural network identifier for dynamic systems is presented. The solution is constructed by using Barrier Lyapunov Functions, Attractive Ellipsoid Method and Riccati equations. The structure of neural network identifier is described, the main theorem on the stability of the system dynamics in deviations between the real and estimated state is proved. The result of this work may be useful in control design for constrained systems wit unknown right-hand side.

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