Exact Controllability of Hemivariational Inequalities in Banach spaces

IF 1.7 2区 数学 Q2 MATHEMATICS, APPLIED
Bholanath Kumbhakar, Dwijendra Narain Pandey
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引用次数: 0

Abstract

The paper is concerned with the exact controllability of the problems described by an evolution of hemivariational inequalities within the framework of reflexive state spaces and uniformly convex control spaces, where the controls are drawn from the space \(L^p(I, U)\), \(~1<p<\infty \). We first introduce an appropriate definition for solutions to the hemivariational inequality problem, as this has not been previously established in the literature. Using this solution framework, we demonstrate that the solutions of the associated differential inclusion problem involving the Clarke subdifferential operator also serve as solutions to the original problem. Consequently, we establish the exact controllability of the original problem through the exact controllability of the corresponding differential inclusion problem. This work presents a novel approach by assuming that the control space U is a uniformly convex Banach space, which helps resolve challenges related to convexity in constructing the necessary control–a difficulty that does not arise when U is a separable Hilbert space.

Banach空间中半变分不等式的精确可控性
本文讨论了在自反状态空间和一致凸控制空间框架内由半变不等式演化所描述的问题的精确可控性,其中控制来自空间\(L^p(I, U)\), \(~1<p<\infty \)。我们首先为半变分不等式问题的解引入一个适当的定义,因为这在以前的文献中没有建立。利用这个解框架,我们证明了涉及Clarke子微分算子的相关微分包含问题的解也可以作为原始问题的解。因此,我们通过相应的微分包含问题的精确可控性来建立原问题的精确可控性。这项工作提出了一种新的方法,假设控制空间U是一个一致凸的巴拿赫空间,这有助于解决在构造必要的控制时与凸性相关的挑战-当U是可分离的希尔伯特空间时不会出现的困难。
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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
103
审稿时长
>12 weeks
期刊介绍: The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.
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