Optimization of dynamic control systems using water cycle algorithm

Abstract

In this paper, path optimization in dynamic control systems was performed using water cycle algorithm. The core principles and assumptions that guide the suggested technique are drawn from nature and are based on observations of the water cycle process and how rivers and streams naturally flow into the sea. The Water Cycle Algorithm has been recognized as a reliable method for dealing with large-scale optimization challenges, largely because of its proficient exploitation and exploration capabilities. This Algorithm does not require the continuity of functions when specifying the issue, unlike many gradient-based approaches. This is achieved through the use of a simple mathematical model that represents the water cycle process. This model is used to simulate the movement of water droplets in a cloud, where each water droplet represents a potential solution to the optimization problem. Although water cycle optimization has been utilized successfully to tackle optimization issues, this is the first time dynamic control optimization has been used. The control problem is switched out for an optimum programming problem in order to find optimal pathways utilizing the Shifted Chebyshev polynomial. The water cycle method was then used to resolve the new issue. The numerical results demonstrate the excellent precision with which this search method can discover solutions.