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arXiv 1603.04562math.OC
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抛物分布参数控制系统的一种基于协方差的核Optimization方法

A Gradient-based Kernel Optimization Approach for Parabolic Distributed Parameter Control Systems

Zhigang Ren, Chao Xu, Qun Lin, Ryan Loxton

摘要:

针对具有边界控制的抛物型分布参数系统,提出了一种新的基于梯度的优化设计方法。与传统的抛物型方程的核最优化方法不同,我们的新方法不需要求解非标准的Riccati型或Klein-Gorden型偏微分方程(PDE)。相反,反馈核被参数化为二阶多项式,其系数是通过基于梯度的动态最优化调整的决策变量,其中系统成本泛函的梯度(其惩罚核和输出幅度)通过求解标准形式的所谓的共态PDE来计算。对核系数施加特殊约束,以确保在温和的条件下,优化的核产生闭环稳定性。数值模拟验证了该方法的有效性。

英文摘要:

This paper proposes a new gradient-based optimization approach for designing optimal feedback kernels for parabolic distributed parameter systems with boundary control. Unlike traditional kernel optimization methods for parabolic systems, our new method does not require solving non-standard Riccati-type or Klein-Gorden-type partial differential equations (PDEs). Instead, the feedback kernel is parameterized as a second-order polynomial whose coefficients are decision variables to be tuned via gradient-based dynamic optimization, where the gradient of the system cost functional (which penalizes both kernel and output magnitude) is computed by solving a so-called costate PDE instandard form. Special constraints are imposed on the kernel coefficients to ensure that, under mild conditions, the optimized kernel yields closed-loop stability. Numerical simulations demonstrate the effectiveness of the proposed approach.

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