固定翼无人机编队集结控制算法研究

针对固定翼无人机协同作战时的编队集结问题,提出了一种新的路径规划和位置分配方法,并设计了包括航迹跟踪、高度保持和速度控制在内的自动驾驶仪。该路径规划算法通过矩阵迭代得到一组较优的目标点分配方案,满足总航程较小和同时到达约束。根据得到的各无人机飞向目标点的航迹,算出无人机编队集结的代价矩阵。在每架无人机确定了应飞航路后,开始沿航路飞向目标点,在此过程中,纵向采用高度保持自动驾驶仪,横向采用航迹跟踪自动驾驶仪,控制无人机按规定航迹飞行。速度调节自动驾驶仪可根据速度指令调节油门大小加减速,跟踪上目标速度,进而实现编队集结。仿真结果验证了所提出的编队集结控制方法的有效性和可行性。     

Adaptive path planning for unmanned aerial vehicles based on bi-level programming and variable planning time interval

This paper presents an adaptive path planner for unmanned aerial vehicles (UAVs) to adapt a real-time path search procedure to variations and fluctuations of UAVs’ relevant performances, with respect to sensory capability, maneuverability, and flight velocity limit. On the basis of a novel adaptability-involved problem statement, bi-level programming (BLP) and variable planning step techniques are introduced to model the necessary path planning components and then an adaptive path planner is developed for the purpose of adaptation and optimization. Additionally, both probabilistic-risk-based obstacle avoidance and performance limits are described as path search constraints to guarantee path safety and navigability. A discrete-search-based path planning solution, embedded with four optimization strategies, is especially designed for the planner to efficiently generate optimal flight paths in complex operational spaces, within which different surface-to-air missiles (SAMs) are deployed. Simulation results in challenging and stochastic scenarios firstly demonstrate the effectiveness and efficiency of the proposed planner, and then verify its great adaptability and relative stability when planning optimal paths for a UAV with changing or fluctuating performances.     

Multi-UAV reconnaissance task allocation for heterogeneous targets using an opposition-based genetic algorithm with double-chromosome encoding

This paper presents a novel multiple Unmanned Aerial Vehicles (UAVs) reconnaissance task allocation model for heterogeneous targets and an effective genetic algorithm to optimize UAVs’ task sequence. Heterogeneous targets are classified into point targets, line targets and area targets according to features of target geometry and sensor’s field of view. Each UAV is regarded as a Dubins vehicle to consider the kinematic constraints. And the objective of task allocation is to minimize the task execution time and UAVs’ total consumptions. Then, multi-UAV reconnaissance task allocation is formulated as an extended Multiple Dubins Travelling Salesmen Problem (MDTSP), where visit paths to the heterogeneous targets must meet specific constraints due to the targets’ feature. As a complex combinatorial optimization problem, the dimensions of MDTSP are further increased due to the heterogeneity of targets. To efficiently solve this computationally expensive problem, the Opposition-based Genetic Algorithm using Double-chromosomes Encoding and Multiple Mutation Operators (OGA-DEMMO) is developed to improve the population variety for enhancing the global exploration capability. The simulation results demonstrate that OGA-DEMMO outperforms the ordinary genetic algorithm, ant colony optimization and random search in terms of optimality of the allocation results, especially for large scale reconnaissance task allocation problems.     

Modeling novel methodologies for unmanned aerial systems–Applications to the UAS-S4 Ehecatl and the UAS-S45 Bálaam

The rising demand for Unmanned Aerial Systems(UASs) to perform tasks in hostile environments has emphasized the need for their simulation models for the preliminary evaluations of their missions. The efficiency of the UAS model is directly related to its capacity to estimate its flight dynamics with minimum computational resources. The literature describes several techniques to estimate accurate aircraft flight dynamics. Most of them are based on system identification. This paper presents an alternative methodology to obtain complete model of the S4 and S45 unmanned aerial systems. The UAS-S4 and the UAS-S45 models were divided into four sub-models, each corresponding to a specific discipline: aerodynamics, propulsion, mass and inertia, and actuator. The‘‘aerodynamic\" sub-model was built using the Fderivatives in-house code, which is an improvement of the classical DATCOM procedure. The ‘‘propulsion\" sub-model was obtained by coupling a two-stroke engine model based on the ideal Otto cycle and a Blade Element Theory(BET) analysis of the propeller. The ‘‘mass and the inertia\" sub-model was designed utilizing the Raymer and DATCOM methodologies. A sub-model of an actuator using servomotor characteristics was employed to complete the model. The total model was then checked by validation of each submodel with numerical and experimental data. The results indicate that the obtained model was accurate and could be used to design a flight simulator.     

Real-time trajectory planning for UCAV air-to-surface attack using inverse dynamics optimization method and receding horizon control

This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle (UCAV) performing autonomous air-to-surface (A/S) attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem (RHC-OCP). In particular, an approximate elliptic launch acceptable region (LAR) model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom (2-DOF) receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.     

翼身融合无人机外形优化设计研究

翼身融合布局无人机具有较好的升阻特性和隐身特性,拥有广泛的应用前景。为了提高无人机的续航能力,兼顾翼身融合无人机的气动特性和结构重量要求,选择无人机升阻比与全机面积作为优化目标,应用多目标优化方法研究翼身融合无人机的外形设计,提出一种针对翼身融合无人机的外形参数化优化设计方法,并进行实例验证。结果表明:外形优化可以提高无人机升阻比、减轻结构重量,从而获得合理的翼身融合无人机设计方案。     

Control techniques of tilt rotor unmanned aerial vehicle systems:A review

The tilt rotor unmanned aerial vehicle (TRUAV) exhibits special application value due to its unique rotor structure. However, varying dynamics and aerodynamic interference caused by tiltable rotors are great technical challenges and key issues for TRUAV's high-powered flight con-trols, which have attracted the attention of many researchers. This paper outlines the concept of TRUAV and some typical TRUAV platforms while focusing on control techniques. TRUAV struc-tural features, dynamics modeling, and flight control methods are discussed, and major challenges and corresponding developmental tendencies associated with TRUAV flight control are summa-rized.     

Cooperative task assignment of multi-UAV system

With the rapid development of Unmanned Aerial Vehicle(UAV) technology, one of the emerging fields is to utilize multi-UAV as a team under autonomous control in a complex environment. Among the challenges in fully achieving autonomous control, Cooperative task assignment stands out as the key function. In this paper, we analyze the importance and difficulties of multiUAV cooperative task assignment in characterizing scenarios and obtaining high-quality solutions.Furthermore, we present three promising directions for future research: Cooperative task assignment in a dynamic complex environment, in an unmanned-manned aircraft system and in a UAV swarm. Our goal is to provide a brief review of multi-UAV cooperative task assignment for readers to further explore.     

无人机中继平台覆盖区域统计模型简

 针对中继信号覆盖区域确定性模型没有考虑信道随机衰落影响的问题,提出了一种基于中断概率的无人机（UAVs）中继平台信号覆盖半径统计模型。通过将中继链路建模为包含路径损耗、阴影衰落和多径衰落的复合分布模型,推导获得中继信号覆盖半径的概率分布,并给出一种利用中断概率数值求解覆盖半径的方法。仿真结果表明,信道衰落对覆盖半径影响非常大,当中断概率小于10%时,覆盖半径仅为无衰落信道时的一半。研究结果对移动自组织网络（MANETs）中的中继网络的无人机最优布置、飞行策略以及网络性能评估等具有重要的参考价值。     

非对称衰落信道下无人机中继传输方案及性能分析

 无人机(UAV)作为中继传输平台受到了国内外研究人员的广泛关注。本文研究了非对称衰落信道下的无人机中继传输系统,提出了输出信噪比最大化准则下的波束形成(BF)优化方案,并推导出系统中断概率、遍历容量和平均误符号率等无线通信系统主要性能指标的理论表达式。通过计算机仿真验证了本文提出的中继传输方案及性能分析的正确性,并定量分析了天线数量、信道参数以及功率分配对系统性能的影响,为无人机中继传输系统的设计及性能评估提供了参考和依据。     

无人机中继平台覆盖区域统计模型

针对中继信号覆盖区域确定性模型没有考虑信道随机衰落影响的问题,提出了一种基于中断概率的无人机（UAVs）中继平台信号覆盖半径统计模型。通过将中继链路建模为包含路径损耗、阴影衰落和多径衰落的复合分布模型,推导获得中继信号覆盖半径的概率分布,并给出一种利用中断概率数值求解覆盖半径的方法。仿真结果表明,信道衰落对覆盖半径影响非常大,当中断概率小于10%时,覆盖半径仅为无衰落信道时的一半。研究结果对移动自组织网络（MANETs）中的中继网络的无人机最优布置、飞行策略以及网络性能评估等具有重要的参考价值。