切比雪夫积分算子的状态和参数估计

R. Zivanovic
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引用次数: 1

摘要

对于一个观测到的非线性系统,需要用微分方程作为系统模型来表述估计问题。我们将这些方程转化为积分方程,并应用积分算子,用切比雪夫插值多项式逼近。非线性估计问题的结果方程是在切比雪夫点网格上离散化的积分方程。用迭代法求解了一系列线性最小二乘问题。网格分辨率可以自动确定,最大限度地提高计算精度。数值效率是通过应用迭代方法,只需要矩阵向量乘法,并通过离散余弦变换的实现,当求解不定积分。相对于条件数大且无界的微分算子公式,该估计算法适用于条件数有界的低矩阵。这一成果对于将该算法应用于典型病态的高阶模型具有重要的实用价值。应用于具有混沌响应的Duffing系统,说明了基于切比雪夫积分算子的估计算法的优越性。
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State and parameter estimation using Chebyshev integral operator
To formulate estimation problem for a observed nonlinear system, differential equations are required as a system model. We recast those equations as integral equations and apply integral operator, which is approximated by Chebyshev interpolating polynomial. Resulting equations of the nonlinear estimation problem are integral equations discretized on the grid of Chebyshev points. A sequence of linear least squares problems are solved iteratively. Grid resolution can be determined automatically to maximize computation accuracy. Numerical efficiency is achieved by applying iterative method that requires only matrix-vector multiplications, and via implementation of Discrete Cosine Transform when solving indefinite integrals. The estimation algorithm works with matrices having bounded low condition number compared to large and unbounded condition number for the formulation with differential operator. This achievement has important practical value when applying the algorithm with high-order models when the differential operator formulation is typically ill-conditioned. Application to a Duffing system having chaotic response, has been used to illustrate advantages of the proposed estimation algorithm based on Chebyshev integral operator.
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