Reduced order modelling of linear time-invariant system using modified cuckoo search algorithm

In this paper modified cuckoo search (MCS) algorithm is considered to develop reduced order model (ROM) of higher-order linear time-invariant systems. Firstly, the MCS algorithm has been employed to minimize the integral square error (ISE) between original and proposed ROM to obtain its unknown coefficients. Five systems of different order are considered to obtain their reduced order model. Finally, various performance indices, such as ISE, integral of absolute and integral of time multiplied by absolute error, have been estimated to reveal the efficacy of the proposed model. Also, time and frequency response characteristics of original higher-order model are compared with the proposed MCS-based and some of other existing techniques-based ROM available in the literature. Furthermore, the results are compared in terms of time response specifications such as rise time (\(t_\mathrm{r} \)) in second, settling time (\( t_\mathrm{s}\)) in second and maximum peak overshoot (\( M_\mathrm{p}\)) in percentage. It is revealed that the response of the proposed MCS-based ROM is much closer to the response of the original higher-order system.