电子电气工程与控制

复合式旋翼飞行器多目标控制分配策略

  • 郑峰婴 ,
  • 刘龙武 ,
  • 程月华 ,
  • 陈志明 ,
  • 成锋娜
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  • 1. 南京航空航天大学 航天学院, 南京 210016;
    2. 南京林业大学 机械电子工程学院, 南京 210037

收稿日期: 2018-10-15

  修回日期: 2018-11-26

  网络出版日期: 2019-03-13

基金资助

国家自然科学基金(61803200,61673206);中央高校基本科研业务费专项资金(NZ2016111);国防科技重点实验室基金(6142220180304)

Multi-objective control allocation strategy of compound rotorcraft

  • ZHENG Fengying ,
  • LIU Longwu ,
  • CHENG Yuehua ,
  • CHEN Zhiming ,
  • CHENG Fengna
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  • 1. College of Aeronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
    2. College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China

Received date: 2018-10-15

  Revised date: 2018-11-26

  Online published: 2019-03-13

Supported by

National Natural Science Foundation of China (61803200,6163206);the Fundamental Research Funds for the Central Universities(NZ2016111);National Defense Science and Technology Fundation of Key Laborory (6142220180304)

摘要

针对复合式旋翼飞行器操纵冗余多模式切换控制问题,提出一种基于赋权多目标混合优化的控制分配策略。该策略根据复合式旋翼飞行器过渡模式舵面操纵特性,建立飞行器带约束过渡过程控制分配模型;设计混合多目标优化性能指标评价函数,有效处理操纵量控制受限、交叉强耦合及非线性特性,并减少舵面耗能;采用改进的粒子群优化算法动态更新操纵量及控制通道的权系数矩阵,提高控制面操纵效率,加快优化搜索速度,快速求解过渡过程多目标控制分配变量。该策略实现复合式旋翼飞行器模式切换过渡过程实时有效地操纵量控制分配,保证飞行器快速准确跟踪控制指令的能力。同时,通过多目标控制分配策略,飞行控制系统不需要增加额外的模式切换控制器,降低系统设计难度,提高安全性。

本文引用格式

郑峰婴 , 刘龙武 , 程月华 , 陈志明 , 成锋娜 . 复合式旋翼飞行器多目标控制分配策略[J]. 航空学报, 2019 , 40(6) : 322727 -322727 . DOI: 10.7527/S1000-6893.2019.22727

Abstract

Aiming at the control plane redundancy of the compound rotorcraft in multi-mode transition process, a control allocation strategy based on weighted multi-objective hybrid optimization is proposed. Drawing on the characteristics of control surfaces in the transition mode, a control allocation model for aircraft with constrained transition procedure is established. A hybrid multi-objective optimization performance index evaluation function is designed, which effectively handle the limitation, the cross strong coupling, and the nonlinear characteristics of control surfaces, and reduces the energy consumption. The improved particle swarm optimization algorithm is used to dynamically update the weight coefficient matrixes of the steering surface manipulation and the control channels, improve the control surface control efficiency, speed up the optimization of the search speed, and quickly solve the steering surface manipulation of the multi-object control allocation in the transition mode. The strategy realizes the real-time effective steering surface control allocation of the compound rotorcraft in the mode switching transition process, ensuring the ability of the aircraft to quickly and accurately track the control commands. At the same time, the multi-objective control allocation makes it unnecessary to extra conversion controllers in the transition mode, reducing the difficulty of the flight control system design and improving the system security.

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