Particle swarm optimization algorithm reinforced fuzzy proportional–integral–derivative for a quadrotor attitude control

Abstract

In this article, the particle swarm optimization algorithm is presented using an improved stochastic variant strategy to optimize the gains of the fuzzy proportional–integral–derivative controller. The particle swarm optimization algorithm aims to renew the elite parameters for the schemes of fuzzy proportional–integral–derivative controls. The integral of time multiplied by absolute error criterion is used to estimate the system performance due to saving the setting and operation time. Facing nonlinear quadrotor attitude control models, the results demonstrate the proposed scheme with better performance.