The Hybrid Maximum Principle for Optimal Control Problems with Spatially Heterogeneous Dynamics is a Consequence of a Pontryagin Maximum Principle for [math]-Local Solutions
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引用次数: 0
Abstract
SIAM Journal on Control and Optimization, Volume 62, Issue 4, Page 2412-2432, August 2024. Abstract. The title of the present work is a nod to the paper “The hybrid maximum principle is a consequence of Pontryagin maximum principle” by Dmitruk and Kaganovich [Systems Control Lett., 57 (2008), pp. 964–970]. We investigate a similar framework of hybrid optimal control problems that is also different from Dmitruk and Kaganovich’s. Precisely, we consider a general control system that is described by a differential equation involving a spatially heterogeneous dynamics. In that context, the sequence of dynamics followed by the trajectory and the corresponding switching times are fully constrained by the state position. We prove with an explicit counterexample that the augmentation technique used by Dmitruk and Kaganovich cannot be fully applied to our setting, but we show that it can be adapted by introducing a new notion of local solution to classical optimal control problems and by establishing a corresponding Pontryagin maximum principle. Thanks to this method, we derive a hybrid maximum principle adapted to our setting, with a simple proof that does not require any technical tools (such as implicit function arguments) to handle the dynamical discontinuities.
SIAM 控制与优化期刊》第 62 卷第 4 期第 2412-2432 页,2024 年 8 月。 摘要。本论文的标题是对 Dmitruk 和 Kaganovich 的论文 "The hybrid maximum principle is a consequence of Pontryagin maximum principle" [Systems Control Lett.我们研究了一个类似的混合最优控制问题框架,它也不同于 Dmitruk 和 Kaganovich 的研究。确切地说,我们考虑的是由涉及空间异质动力学的微分方程描述的一般控制系统。在这种情况下,轨迹所遵循的动力学序列和相应的切换时间完全受状态位置的约束。我们通过一个明确的反例证明,德米特鲁克和卡加诺维奇使用的增强技术不能完全适用于我们的环境,但我们通过引入经典最优控制问题的局部解这一新概念,并建立相应的庞特里亚金最大原则,证明了这一技术是可以调整的。由于采用了这种方法,我们推导出了适合我们的混合最大原理,其证明简单,不需要任何技术工具(如隐函数参数)来处理动态不连续性。
期刊介绍:
SIAM Journal on Control and Optimization (SICON) publishes original research articles on the mathematics and applications of control theory and certain parts of optimization theory. Papers considered for publication must be significant at both the mathematical level and the level of applications or potential applications. Papers containing mostly routine mathematics or those with no discernible connection to control and systems theory or optimization will not be considered for publication. From time to time, the journal will also publish authoritative surveys of important subject areas in control theory and optimization whose level of maturity permits a clear and unified exposition.
The broad areas mentioned above are intended to encompass a wide range of mathematical techniques and scientific, engineering, economic, and industrial applications. These include stochastic and deterministic methods in control, estimation, and identification of systems; modeling and realization of complex control systems; the numerical analysis and related computational methodology of control processes and allied issues; and the development of mathematical theories and techniques that give new insights into old problems or provide the basis for further progress in control theory and optimization. Within the field of optimization, the journal focuses on the parts that are relevant to dynamic and control systems. Contributions to numerical methodology are also welcome in accordance with these aims, especially as related to large-scale problems and decomposition as well as to fundamental questions of convergence and approximation.