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Application of the least squares algorithm to the observer design for linear time-varying systems

机译:最小二乘算法在线性时变系统观测器设计中的应用

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摘要

In this paper, it is shown that the least squares algorithm with covariance reset, which is originally developed for the purpose of constant parameter identification, can be effectively applied to the observer design for a general linear time-varying system. The new observer successfully avoids many of the disadvantages of other time-varying observers, such as slow convergence rate, heavy computation load, high amplification of measurement noise, and the inapplicability to systems with time-varying observability indexes or discontinuous parameter variations.
机译:本文表明,最初为恒定参数识别而开发的带有协方差重置的最小二乘算法可以有效地应用于一般线性时变系统的观测器设计。新的观察者成功地避免了其他时变观察者的许多缺点,例如收敛速度慢,计算量大,测量噪声放大倍数大,以及不适用于具有时变可观察性指标或参数不连续的系统。

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