Аннотация:
Over recent years, bioinspired swarm techniques have gained significant popularity for addressing realworld engineering optimization challenges. One promising application of these methods is developing
and optimizing of intelligent systems, specifically fuzzy control systems. This paper examines research
issues and performs a comparative analysis of bioinspired swarm methods for parameter optimization in
fuzzy control systems. It compares various hybrid modifications of particle swarm optimization and grey
wolf optimization techniques, specifically adapted for fuzzy system parameter optimization, against
traditional search methods. As a case study, the paper uses the parametric optimization of a TakagiSugeno fuzzy control system designed for a quadrotor-type unmanned aerial vehicle (UAV). The
simulation results confirm the effectiveness of the presented swarm bioinspired optimization techniques,
taking into account both the performance of the UAV's fuzzy control system and the computational costs
involved.
