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首页> 外文期刊>International journal on engineering applications >A New Parametric Estimation Algorithm for Large-Scale Systems Described by State-Space Mathematical Models
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A New Parametric Estimation Algorithm for Large-Scale Systems Described by State-Space Mathematical Models

机译:一种新的正国空间数学模型描述的大型系统的参数估计算法

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摘要

This paper is concerned with the parametric estimation problem for large-scale systems composed of several interconnected systems, which are described by linear discrete-time state-space mathematical models with unknown parameters. A new recursive parametric estimation algorithm with a particular adaptive gain is proposed for estimating the interconnected system parameters. The stability analysis of the developed parametric estimation scheme is treated by using the Lyapunov method. The proposed recursive parametric estimation algorithm is applied to estimate the parameters of a large-scale systems composed of three interconnected systems. The obtained numerical simulation results show the good performance of this algorithm.
机译:本文涉及由多个互连系统组成的大型系统的参数估计问题,该互连系统由具有未知参数的线性离散时间空间数学模型描述。 提出了一种具有特定自适应增益的新递归参数估计算法,用于估计互连的系统参数。 通过使用Lyapunov方法处理开发的参数估计方案的稳定性分析。 建议的递归参数估计算法应用于估计由三个互连系统组成的大规模系统的参数。 所获得的数值模拟结果表明了该算法的良好性能。

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