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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2024, Volume 64, Number 4, paper published in the English version journal
(Mi zvmmf11742)
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Papers published in the English version of the journal
Non-quadratic proxy functions in mirror descent method applied to designing of robust controllers for nonlinear dynamic systems with uncertainty
A. V. Nazinab, A. S. Poznyakc a V.A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, 117997, Moscow, Russia
b Moscow Institute of Physics and Technology (National Research University), 141701, Dolgoprudny, Moscow oblast, Russia
c CINVESTAV-IPN, Av. IPN, 2508, CP, 07360, CD Mexico, Mexico
Abstract:
We consider a class of controlled nonlinear plants, the dynamics of which are governed by a vector system of ordinary differential equations with a right-hand side that is partially known. The study’s objective is to construct a robust tracking controller with certain constraints on the state variables, assuming that the state variables and their time derivatives can be observed. The Legendre–Fenchel transform and a chosen proxy function are utilized to develop this mathematical development using the mirror descent approach, which is frequently employed in convex optimization problems involving static objects. The Average Subgradient Method (an improved version of the Subgradient Descent Method), and the Integral Sliding Mode technique for continuous-time control systems are basically extended by the suggested unifying architecture. The primary findings include demonstrating that the “desired regime”– a non-stationary analog of the sliding surface – can be achieved from the very start of the process and getting an explicit upper bound on the cost function’s decrement.
Key words:
mirror descent method, robust tracking, convergence state, convex constrained optimization, sliding mode.
Received: 07.10.2023 Revised: 25.10.2023 Accepted: 07.06.2024
Citation:
A. V. Nazin, A. S. Poznyak, “Non-quadratic proxy functions in mirror descent method applied to designing of robust controllers for nonlinear dynamic systems with uncertainty”, Comput. Math. Math. Phys., 64:4 (2024), 820–832
Linking options:
https://www.mathnet.ru/eng/zvmmf11742
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