基于神经网络的多四旋翼保性能编队控制  

Guaranteed Performance Formation Control of Multi-quadrotor Based on Neural Network

作　　者：曹志斌 邵星灵[2] 杨卫[2] 康新晨 CAO Zhi-bin;SHAO Xing-ling;YANG Wei;KANG Xin-chen(Guilin University of Aerospace Technology, School of Electronic Information and Automation, Guilin 541004, China;Key Lab of Instrumentation Science & Dynamic Measurement, Ministry of Education, North University of China, Taiyuan 030051, China)

机构地区：[1]桂林航天工业学院电子信息与自动化学院,桂林541004 [2]中北大学仪器科学与动态测试教育部重点实验室,太原030051

出　　处：《科学技术与工程》2022年第15期6347-6353,共7页Science Technology and Engineering

基　　金：国家自然科学基金(61841101);广西科技重大专项(桂科AA17204086);广西高校中青年教师科研基础能力提升项目(2021KY0788)。

摘　　要：针对多四旋翼编队飞行过程中存在的参数和外界扰动不确定性导致编队系统不稳定问题,设计了一种多四旋翼分布式神经自适应动态面协同编队控制方法。采用学习维数低、实时性强的最小参数学习神经网络观测器,实现对四旋翼位置回路和角度回路未知非线性干扰的快速平滑学习与补偿。利用预设性能控制方法将原先受约束的同步误差经转换函数变换为不受约束的误差,解决协同编队中的位置一致性控制问题,确保各四旋翼位置跟踪同步误差能够按照预设的收敛速度、超调量及稳态误差收敛至期望的区域。仿真实验表明,所提多四旋翼协同抗干扰编队方法在较大扰动环境下仍能达到良好的控制效果。A distributed neural adaptive formation control method was proposed for multiple quad-rotors to solve the problem of formation system instability caused by uncertainties of parameters and external disturbances.A minimum learning parameter based neural network observer with strong real-time calculation and low learning dimension was used to realize smooth and fast online learning and compensation of unknown nonlinear disturbance in the position loop and angle loop of quad-rotors.By using the prescribed performance control,the constrained synchronization error was converted into unconstrained error through the error conversion function to solve the position consistency control problem in cooperative formation,and ensure that the position tracking synchronization error of each quadrotor can converge to the desired region according to the preset convergence speed,overshoot and steady-state error.Simulation results show that the proposed formation controller has good control performance even in large disturbance environment.

关 键 词：协同编队 四旋翼无人机 神经网络 预设性能 

分 类 号：V279[航空宇航科学与技术—飞行器设计]