Chaotic grey wolf optimization-based active disturbance rejection control applied to quadrotor trajectory tracking

In this paper, a new active disturbance rejection control (ADRC) scheme based on swarm intelligent method is proposed for quadrotors to achieve position tracking and attitude stabilization. First, the finite-time convergent extended state observer (FTCESO) is designed to enhance the performance of ADRC controller. Then, the chaotic grey wolf optimization (CGWO) algorithm is developed with chaos initialization and chaos search to obtain the optimal parameters of attitude and position controllers. Numerical simulations are presented to demonstrate the effectiveness of the CGWO-based ADRC scheme.