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Numerically robust synthesis of discrete-time H{sub}∞ estimators based on dual J-lossless factorisations

机译:基于双重J无损分解的离散时间H {sub}∞估计的数值鲁棒综合

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摘要

An approach to the numerically reliable synthesis of the H{sub}∞ suboptimal state estimators for discretised continuous-time processes is presented. The approach is based on suitable dual J-lossless factorisations of chain-scattering representations of estimated processes. It is demonstrated that for a sufficiently small sampling period the standard forward shift operator techniques may become ill-conditioned and numerical robustness of the design procedures can be significantly improved by employing the so-called delta operator models of the process. State-space models of all H{sub}∞ sub-optimal estimators are obtained by considering the suitable delta-domain algebraic Riccati equation and the corresponding generalised eigenproblem formulation. A relative condition number of this equation is used as a measure of its numerical conditioning. Both regular problems concerning models having no zeros on the boundary of the delta-domain stability region and irregular (non-standard) problems of models with such zeros are examined. For the first case, an approach based on a dual J-lossless factorisation is proposed while in the second case an extended dual J-lossless factorisation based on a zero compensator technique s required. Two numerical examples are given to illustrate some properties of the considered delta-domain approach.
机译:提出了一种用于离散连续时间过程的H {sub}∞次优状态估计的数值可靠综合方法。该方法基于估计过程的链散布表示的适当双重J无损分解。结果表明,对于足够小的采样周期,标准的前移运算符技术可能会变得不适,并且可以通过采用所谓的过程三角运算符模型来显着提高设计过程的数值鲁棒性。通过考虑合适的δ域代数Riccati方程和相应的广义特征问题公式,获得所有H {sub}∞次优估计量的状态空间模型。该方程式的相对条件号用作其数值条件的量度。既检查了在增量域稳定区域边界上不存在零的模型的常规问题,也检查了具有此类零的模型的不规则(非标准)问题。对于第一种情况,提出了一种基于双J无损分解的方法,而在第二种情况下,则需要基于零补偿器技术的扩展双J无损分解。给出两个数值示例,以说明所考虑的增量域方法的某些属性。

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