Information Technology for Parametric Optimization of Fuzzy Systems Based on Hybrid Grey Wolf Algorithms

In recent years, bioinspired multi-agent techniques have become very popular for solving real-life engineering optimization problems. One of the promising areas of using these methods is their application for the development and optimization of intelligent systems, in particular, fuzzy control and decision-making systems. This paper presents the development and study of information technology for parametric optimization of different types of fuzzy systems (FS) based on the combination of improved grey wolf algorithm and local search techniques. The proposed information technology allows to conduct effective optimization of various parameters of FSs, finding the optimal solution of the problem, and, at the same time, has a higher convergence rate compared with the technologies that use basic and improved grey wolf algorithms. The effectiveness study of the proposed information technology is carried out at a simulation experiment on parametric optimization of a fuzzy control system for the quadrotor unmanned aerial vehicle. The obtained simulation results confirm the high efficiency of the developed information technology based on hybrid improved grey wolf algorithm, as well as the feasibility of its use for parametric optimization of the fuzzy control and decision-making systems of various types and configurations. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.