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Feedback Necessary Optimality Conditions for Nonlinear Measure-Driven Processes ?

机译:反馈必要的非线性测量驱动过程的最优性条件

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We consider a non-convex optimal impulsive control problem for nonlinear differential equations, driven by vector-valued Borel measures, under no commutativity assumptions of the Frobenius type. For this problem, we derive nonlocal necessary optimality conditions operating with a specific class of impulsive feedback controls, generated by certain functions of the Lyapunov type. These feedback controls are constructed in a way similar to the dynamical programming, but with the use of weakly monotone solutions to the corresponding Hamilton-Jacobi equation, instead of the Bellman’s function. We offer the notion of weakly monotone function with respect to a measure-driven differential equation, and give constructive criteria for this type of monotonicity. Based on a space-time representation of impulsive processes, we propose the concept of impulsive feedback control and present nonlocal necessary optimality conditions, which are shown to filter out non-optimal extrema of the impulsive Maximum Principle.
机译:我们考虑了非线性微分方程的非凸出的最佳脉冲控制问题,由矢量值硼尔措施驱动,在Frobenius型的不换向假设下。对于这个问题,我们通过Lyapunov类型的某些功能产生了与特定类脉冲反馈控制操作的非局部必要的最优性条件。这些反馈控制以类似于动态编程的方式构建,而是利用弱单调的解决方案与相应的Hamilton-Jacobi方程,而不是Bellman的功能。我们提供关于测量驱动的微分方程的弱单调功能的概念,并为这种类型的单调性提供建设性标准。基于脉冲过程的时空表示,我们提出了脉冲反馈控制的概念,并存在于非局部必要的最优性条件,这被示出了滤除脉冲最大原理的非最佳极值。

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