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

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.