Geometric Methods for Adjoint Systems

IF 2.6 2区 数学 Q1 MATHEMATICS, APPLIED
Brian Kha Tran, Melvin Leok
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Abstract

Adjoint systems are widely used to inform control, optimization, and design in systems described by ordinary differential equations or differential-algebraic equations. In this paper, we explore the geometric properties and develop methods for such adjoint systems. In particular, we utilize symplectic and presymplectic geometry to investigate the properties of adjoint systems associated with ordinary differential equations and differential-algebraic equations, respectively. We show that the adjoint variational quadratic conservation laws, which are key to adjoint sensitivity analysis, arise from (pre)symplecticity of such adjoint systems. We discuss various additional geometric properties of adjoint systems, such as symmetries and variational characterizations. For adjoint systems associated with a differential-algebraic equation, we relate the index of the differential-algebraic equation to the presymplectic constraint algorithm of Gotay et al. (J Math Phys 19(11):2388–2399, 1978). As an application of this geometric framework, we discuss how the adjoint variational quadratic conservation laws can be used to compute sensitivities of terminal or running cost functions. Furthermore, we develop structure-preserving numerical methods for such systems using Galerkin Hamiltonian variational integrators (Leok and Zhang in IMA J. Numer. Anal. 31(4):1497–1532, 2011) which admit discrete analogues of these quadratic conservation laws. We additionally show that such methods are natural, in the sense that reduction, forming the adjoint system, and discretization all commute, for suitable choices of these processes. We utilize this naturality to derive a variational error analysis result for the presymplectic variational integrator that we use to discretize the adjoint DAE system. Finally, we discuss the application of adjoint systems in the context of optimal control problems, where we prove a similar naturality result.

Abstract Image

用于邻接系统的几何方法
在由常微分方程或微分代数方程描述的系统中,邻接系统被广泛用于为控制、优化和设计提供信息。在本文中,我们将探索此类邻接系统的几何特性并开发相关方法。特别是,我们利用交错几何和前交错几何分别研究了与常微分方程和微分代数方程相关的邻接系统的性质。我们证明,作为邻接灵敏度分析关键的邻接变分二次守恒律,产生于此类邻接系统的(前)交折性。我们还讨论了邻接系统的各种其他几何特性,如对称性和变分特性。对于与微分代数方程相关的邻接系统,我们将微分代数方程的指数与 Gotay 等人的预交映约束算法联系起来(J Math Phys 19(11):2388-2399, 1978)。作为这一几何框架的应用,我们讨论了如何利用邻接变分二次守恒定律来计算终端或运行成本函数的敏感性。此外,我们还利用 Galerkin Hamiltonian 变分积分器为此类系统开发了保结构数值方法(Leok 和 Zhang 在 IMA J. Numer.Anal.31(4):1497-1532,2011),这些方法允许这些二次守恒定律的离散类比。我们还证明了这些方法的自然性,即对于这些过程的适当选择,还原、形成邻接系统和离散化都是相通的。我们利用这种自然性推导出了用于离散化邻接 DAE 系统的前折中变分积分器的变分误差分析结果。最后,我们讨论了邻接系统在最优控制问题中的应用,并证明了类似的自然性结果。
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来源期刊
CiteScore
5.00
自引率
3.30%
发文量
87
审稿时长
4.5 months
期刊介绍: The mission of the Journal of Nonlinear Science is to publish papers that augment the fundamental ways we describe, model, and predict nonlinear phenomena. Papers should make an original contribution to at least one technical area and should in addition illuminate issues beyond that area''s boundaries. Even excellent papers in a narrow field of interest are not appropriate for the journal. Papers can be oriented toward theory, experimentation, algorithms, numerical simulations, or applications as long as the work is creative and sound. Excessively theoretical work in which the application to natural phenomena is not apparent (at least through similar techniques) or in which the development of fundamental methodologies is not present is probably not appropriate. In turn, papers oriented toward experimentation, numerical simulations, or applications must not simply report results without an indication of what a theoretical explanation might be. All papers should be submitted in English and must meet common standards of usage and grammar. In addition, because ours is a multidisciplinary subject, at minimum the introduction to the paper should be readable to a broad range of scientists and not only to specialists in the subject area. The scientific importance of the paper and its conclusions should be made clear in the introduction-this means that not only should the problem you study be presented, but its historical background, its relevance to science and technology, the specific phenomena it can be used to describe or investigate, and the outstanding open issues related to it should be explained. Failure to achieve this could disqualify the paper.
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