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Network-based Iterative Learning Control Approaches with Communication Delay Adjustment Factors for LTI Systems

机译:LTI系统中具有通信延迟调整因子的基于网络的迭代学习控制方法

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The paper develops two novel network-based iterative learning control approaches with communication delay adjustment factors for SISO LTI systems. Suppose that communication delay is subject to 0-1 Bernoulli distribution. In these two approaches, the actual system input is synchronous at the previous iteration if the system input is delayed at the current iteration, otherwise it is a linear combination of the synchronous system inputs at the current and previous iterations, where the coefficients are dependent upon the input communication delay probability. Two strategies are given for the output signals used by the ILC unit. One is the same as that for the actual system input; as for the other one, the actually utilized output is the synchronous desired output if the system output is delayed, otherwise it is a linear combination of the synchronous system output at the current iteration and the synchronous desired output, where the coefficients are dependent upon the output communication delay probability. It is shown that the expectation of the system output is convergent to the desired output under certain conditions. Finally, we use an example to illustrate the effectiveness of the developed NILC approaches.
机译:本文针对SISO LTI系统开发了两种具有通信延迟调整因子的新颖的基于网络的迭代学习控制方法。假设通信延迟服从0-1伯努利分布。在这两种方法中,如果系统输入在当前迭代中被延迟,则实际系统输入在前一迭代中是同步的,否则,它是当前和先前迭代中的同步系统输入的线性组合,其中系数取决于输入通信延迟概率。对于ILC单元使用的输出信号,给出了两种策略。一个与实际系统输入的相同;至于另一个,如果系统输出被延迟,则实际使用的输出是同步期望输出,否则它是当前迭代中的同步系统输出与同步期望输出的线性组合,其中系数取决于输出通信延迟概率。结果表明,在某些条件下,系统输出的期望值收敛到期望的输出值。最后,我们用一个例子来说明已开发的NILC方法的有效性。

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