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A Dilated LMI Approach to Robust Performance Analysis of Linear Time-Invariant Uncertain Systems

机译:一种扩张的LMI方法,促进线性时间不变不确定系统的鲁棒性能分析

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This paper studies LMI-based robust performance analysis of linear time-invariant systems depending on uncertain parameters. In the case where the coefficient matrices of the system are affine with respect to the uncertain parameters, the standard LMI's are helpful in dealing with such analysis problems provided that we accept the notion of quadratic stability. On the other hand, in the case of rational parameter dependence, the standard LMI's carry some deficiency and thus we need another effort to derive numerically tractable conditions. This paper shows that recently developed dilated LMI's are effective in attacking such robust performance analysis problems. Indeed, applying dilated LMI's leads directly to numerically tractable conditions regardless of the form of the dependence on uncertain parameters. In addition, dilated LMI's enable us to employ parameter-dependent Lyapunov variables to test robust performance, which are known to be quite effective to alleviate the conservatism resulting from a quadratic (parameter-independent) Lyapunov variable.
机译:本文根据不确定参数研究基于LMI的鲁棒性能分析线性时间不变系统。在系统的系数矩阵相对于不确定参数的情况下,标准LMI有助于处理这些分析问题,所以提供了我们接受二次稳定性的概念。另一方面,在理性参数依赖的情况下,标准LMI携带一些缺陷,因此我们需要另一种努力来导出数值易易造型的条件。本文展示最近开发的扩张LMI在攻击这种稳健的性能分析问题方面是有效的。实际上,无论对不确定参数的依赖性的形式如何,将扩张的LMI的导线直接施加到数值上。此外,扩张LMI的LMI使我们能够采用参数依赖的Lyapunov变量来测试强大的性能,这已知是非常有效地减轻由二次(参数无关)Lyapunov变量产生的保守主义。

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