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Generalization of Piecewise Constant Approximation in the L/L2 Optimal Control of Sampled-Data Systems

机译:L / L 2 采样数据系统最优控制中的分段常数逼近的广义化

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This paper is concerned with the L/L2 -induced norm of linear time-invariant (LTI) sampled-data systems, i.e., the induced norm from L2 to L in LTI sampled-data systems. In our preceding studies, the idea of piecewise constant approximation has been developed for analyzing and minimizing the L/L2 -induced norm in LTI sampled-data systems via the fast-lifting technique together with the Taylor expansion of relevant functions, and it is shown that the piecewise constant approximation has the convergence rate of 1/ N for both the analysis and minimization problems with respect to the fast-lifting parameter N. Along this line, this paper develops a generalized scheme to the piecewise constant approximation by taking advantage of the freedom in the point around which associated functions are expanded to Taylor series. It is further shown in this paper that even though the piecewise constant approximation has the convergence rate of 1/ N regardless of the point at which the Taylor expansion is applied, we can obtain a new discretization method for LTI sampled-data systems with quantitatively improved accuracies than those in the preceding studies for both the analysis and minimization problems through the generalization scheme.
机译:本文与L有关 /升 2 时不变(LTI)采样数据系统的归纳范数,即L的归纳范数 2 到L 在LTI采样数据系统中。在我们之前的研究中,已经提出了分段常数逼近的概念,用于分析和最小化L。 /升 2 快速提升技术结合相关函数的泰勒展开在LTI采样数据系统中引入归一化范数,并且表明对于分析和最小化问题,分段常数逼近的收敛速度为1 / N沿着这条线,本文利用相关函数扩展为泰勒级数的点的自由度,将其发展为一种分段常数近似的广义方案。本文进一步表明,即使分段常数近似的收敛速度为1 / N,无论采用泰勒展开的点如何,我们都可以得到一种定量改进的LTI采样数据系统的离散化方法。通过泛化方案在分析和最小化问题上的准确性都比以前的研究更高。

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