Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/92214
Title: Robust methods for stabilization of Hamiltonian systems in economic growth models
Authors: Tarasyev, A.
Usova, A.
Issue Date: 2018
Publisher: Elsevier B.V.
Citation: Tarasyev A. Robust methods for stabilization of Hamiltonian systems in economic growth models / A. Tarasyev, A. Usova. — DOI 10.1016/j.ifacol.2018.11.344 // IFAC-PapersOnLine. — 2018. — Vol. 32. — Iss. 51. — P. 7-12.
Abstract: The paper discusses the existence of a linear manifold in a vicinity of a steady state for stabilization of the Hamiltonian systems arising in optimal control problems for economic growth models. It is shown that such stable manifold exists for almost all possible values of model parameters guaranteeing the existence of a steady state. Research is based on the qualitative analysis of the Hamiltonian dynamics, which plays a key role for investigating the asymptotic behavior of optimal trajectories. A procedure is proposed for stabilization of the Hamiltonian system, whose trajectories converge to equilibrium and approximate the optimal solution with the quadratic accuracy at a vicinity of the steady state. Basing on properties of the Hamiltonian matrices, the classification of steady states is provided and the sensitivity analysis for identification of their character is implemented with respect to model parameters. The proposed approach is applied to the model dealing with dynamic optimization of the resource productivity. © 2018
Keywords: GROWTH MODELS
HAMILTONIAN SYSTEM
OPTIMAL CONTROL
STABILIZATION
STABLE MANIFOLD
ECONOMICS
OPTIMAL CONTROL SYSTEMS
SENSITIVITY ANALYSIS
STABILIZATION
ECONOMIC GROWTH MODELS
GROWTH MODELS
HAMILTONIAN SYSTEMS
OPTIMAL CONTROL PROBLEM
OPTIMAL CONTROLS
OPTIMAL TRAJECTORIES
RESOURCE PRODUCTIVITY
STABLE MANIFOLD
HAMILTONIANS
URI: http://elar.urfu.ru/handle/10995/92214
Access: info:eu-repo/semantics/openAccess
RSCI ID: 37208002
SCOPUS ID: 85058235073
WOS ID: 000453278300003
PURE ID: 8425015
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2018.11.344
Sponsorship: 18–01–00221a
The paper is supported by Russin Foundation for Basic Research (Project No. 18–01–00221a).
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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