GWO Based Reduced-Order Modeling of Doha Water Treatment Plant

Uncertainty in system parameters can have major impact on system performance. So, uncertainty should be considered while analyzing the performance of system. The uncertainty can be included by considering model as interval system. This study develops an interval model for Doha water treatment system. Firstly, interval model is obtained while considering finite range of uncertainty in transfer function. Then, order reduction method is applied to reduce the order of interval system. To derive the model, an objective function is designed which is a function of time moments and Markov parameters. The objective function minimization is obtained through grey wolf optimization (GWO) algorithm. The GWO is found to be very effective in exploring and exploiting the search space. Due to this, the GWO is considered for minimization of objective function in this study. The results obtained support the efficacy and effectiveness of GWO for minimization of objective function designed for model reduction of interval system of Doha treatment plant.