基于变权重变异鸽群优化的无人机空中加油自抗扰控制器设计

针对空中加油过程中的受油机模型建模误差和强扰动以及自抗扰控制器（ADRC）人工参数整定难的问题，提出了一种基于变权重变异鸽群优化（VWMPIO）算法的无人机自抗扰控制器优化算法。首先，给出了六自由度无人机（UAV）模型，基于自抗扰控制结构设计了一种受油机的姿态控制器，在此基础上用所提出的变权重变异鸽群优化算法整定了自抗扰控制器参数。随后，将变权重变异鸽群优化与其他基本鸽群优化算法、粒子群优化算法进行了实验对比，并从控制性能和抗噪声性能的角度对自抗扰控制器和传统的比例-微分-积分（PID）控制器进行了仿真对比。实验结果表明所提算法能提高复杂态势环境下无人机空中加油的控制精度和扰动抑制性能。

ADRC controller design for UAV based on variable weighted mutant pigeon inspired optimization

This paper addresses the various modeling errors and external disturbances in the process of aerial refueling and the difficulty of manual parameter setting of Active Disturbance Rejection Controller (ADRC) controllers. A Variable Weighted Mutant Pigeon Inspired Optimization (VWMPIO) algorithm for ADRC designed for Unmanned Aerial Vehicle (UAV) is proposed. First of all, this paper establishes a six degree-of-freedom UAV model and then designs an attitude controller based on the ADRC structure. On this basis, parameters of the controller are tuned with the VWMPIO algorithm proposed in this paper, and a comparison amongst the VWMPIO algorithm, the basic PIO algorithm, and the PSO optimization algorithms. In addition, the ADRC controller is compared with the traditional Proportional-Integral-Differential (PID) controller in terms of control performance and anti-noise performance. The experimental result shows that the proposed method can improve the control accuracy and disturbance rejection performance of UAV aerial refueling in complex situations.