In this study, the Improved Water Swirl Algorithm (IWSA) is used to formulate a lower order Multi Input Multi Output (MIMO) model in transfer function form for a given perfectly stable higher order MIMO Continuous system. The Water Swirl Algorithm (WSA) is a swarm-based optimization algorithm that replicates how water finds its way to a sink drain. It analyses the flow and searching behaviour of water for drains and presents appropriate strength update equations for iteratively finding the best solution from a randomly generated search space. The boundary limitations restricting the search space are represented by the sink retaining the water particle. The strength of a water particle is determined by three factors: inertia, cognition, and social interaction. For all living things, water is an unavoidable ingredient in nature. The cognitive component of a water particle is split into two parts in the proposed Improved WSA: a good experience component and a worst experience component. The particle can bypass the previously visited worst spot and try to occupy the best position due to the inclusion of the worst experience component. This work proposes a weighted average method for reducing a higher order model formulation to a lower order one. The lower order model is chosen using the integral square error as a criterion. For commonizing the denominators of the individual lower order approximants so that a lower order MIMO model can be reported in the transfer function matrix form, an average approach has been developed. An example is used to demonstrate the proposed methodology.
Author (S) Details
Department of Electrical and Electronics Engineering, Anna University Regional Centre, Coimbatore, India.
Department of Electrical and Electronics Engineering, Government College of Technology, Coimbatore, India.
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