Model Order Reduction of Linear Continuous and Discrete Systems Using Grey Wolf Optimization

The Single Input Single Output (SISO) continuous and discrete time system is reduced through evolutionary technique to a lower order model in this study. The Grey Wolf Optimization approach (GWO) is used in the evolutionary process method to minimize the higher model. The foundation of GWO approach is based on the Integral Square Error (ISE), which measures the disparity between the transient responses of the original higher order model and the lower order model when a unit step input is applied. If the initial high order system is stable and of equivalent quality to other well-known existing order reduction approaches, the suggested technique ensures stability of the reduced model. Four numerical examples, two for continuous time and two for discrete time, are used to demonstrate the approach.