SCA Assisted Reduced-Order Modelling of Interval Modelled Doha Water Treatment Plant

The performance of the system is affected by parameter variations. The parameter variations can effectively be analysed by interval system. In this work, Doha water treatment plant is modeled as interval system. After this, reduced-order modeling is accomplished for such interval modeled Doha water treatment plant. Initially, uncertainty is considered in each coefficient of the transfer function to obtain the interval model of Doha water treatment plant. Later, time moments and Markov parameters are utilized to determine the reduced-order model of obtained interval modeled Doha water treatment plant. An error function is formed in between time moments and Markov parameters for the determination of reduced-order model. Sine-cosine algorithm (SCA) is used for minimization of thus obtained error function. SCA is population-based stochastic optimization technique which uses sine and cosine functions for the exploration and exploitation of search space to find the solutions. The analysis of results shows that reduced-order model is effectively describing and approaching the response of the system under consideration.