Implementation of Crow Search Algorithm for Achieving Optimal Control of a Single-Link Flexible Manipulator

Abstract

A metaheuristic optimizer based on the cognitive behavior of crows, called the Crow Search Algorithm (CSA), is suggested in this paper for the optimization of the performance of the single link flexible manipulator as a constrained optimal control problem, which comprises objective functions, constraints, and decision variables. The CSA outperformed other algorithms, such as Differential Evolution, Grey Wolf Optimization, and Particle Swarm Optimization. Parameter setting is another highlight of the current paper. In conclusion, CSA yields more promising results than other approaches.