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Adaptive observer with exponential forgetting factor for linear time varying systems

机译:具有线性时变系统的指数遗忘因子的自适应观测器

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For the purpose of recursive joint estimation of state and parameters in continuous-time state space systems, the algorithm proposed in this paper improves the consistency of an adaptive observer for multi-input-multi-output (MIMO) linear time varying (LTV) systems. The new algorithm makes use of a time varying gain matrix for parameter estimation, instead of the constant gain matrix used by the previously reported algorithm. It is exponentially stable, converges in the mean for both state and parameter estimations. The covariance matrix of the parameter estimation error can be made arbitrarily small by choosing a sufficiently small forgetting factor.
机译:出于递归联合估计连续时间状态空间系统中状态和参数的目的,本文提出的算法提高了多输入多输出(MIMO)线性时变(LTV)系统的自适应观测器的一致性。 。新算法将时变增益矩阵用于参数估计,而不是先前报告的算法使用的恒定增益矩阵。它是指数稳定的,在状态和参数估计的均值中收敛。通过选择足够小的遗忘因子,可以任意地减小参数估计误差的协方差矩阵。

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