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A State Predictor for Multivariable Systems Including Multiple Delays in Each Output Path

机译:多变量系统的状态预测器,每个输出路径中包含多个延迟

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Various practical systems include time delays due to measurement and computational delays, and transmission and transport lags. In this paper, the authors propose a novel state predictor for a certain class of multivariable systems including multiple output delays. The predictor consists of full-order observers estimating past state from each delayed output and finite interval integrators compensating the effect of the delays using state transition equations. State prediction error converges to zero at an arbitrary rate, which can be determined by choosing a finite number of poles of the full-order observers. In this predictor, the distance to instability of the state transition matrix is not affected by the delays. This means that large delays have no influence on the numerical stability, whereas that of a conventional observer highly depends on the delays. Numerical examples for an integral process and an unstable process demonstrate the effectiveness of the proposed predictor.
机译:各种实际系统包括由于测量和计算延迟而引起的时间延迟以及传输和传输滞后。在本文中,作者为包含多个输出延迟的一类多变量系统提出了一种新颖的状态预测器。预测器包括从每个延迟的输出中估计过去状态的全序观测器,以及使用状态转换方程补偿延迟影响的有限间隔积分器。状态预测误差以任意速率收敛到零,这可以通过选择有限数量的全阶观测器的极点来确定。在该预测变量中,状态转移矩阵到不稳定性的距离不受延迟的影响。这意味着大的延迟不会影响数值稳定性,而传统观察者的延迟高度依赖于延迟。积分过程和不稳定过程的数值例子证明了所提出的预测器的有效性。

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