Metaheuristic Solution for Stability Analysis of Nonlinear Systems Using an Intelligent Algorithm with Potential Applications

In this article, we provide a metaheuristic-based solution for stability analysis of nonlinear systems. We identify the optimal level set in state space these systems by combining two optimization phases. This is definite negative region time derivative polynomial Lyapunov function (LF). Then, consider global problem stated The first phase an external to search positive LF, whose under linear matrix inequalities. candidate LF coefficients are adjusted using Jaya metaheuristic algorithm. second internal ensure accurate estimate attraction each that optimized externally. key idea algorithm based mainly on optimization, which provides efficient way characterize accurately volume and shape maximal domains. conduct numerical experiments validate proposed approach. Two potential real-world applications proposed.