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.     

Numerical study on flow control of ship airwake and rotor airload during helicopter shipboard landing

A numerical study on flow control of ship airwake during shipboard landing is carried out to address the effect of flow control devices on helicopter rotor airload. The in-house Reynolds Averaged Navier-Stokes (RANS) based solver Rotorcraft AeroDynamics and Aeroacoustics Solver (RADAS), with combination of momentum source approach is employed to conduct the helicopter shipboard landing simulation. The control effects of three aerodynamic modifications of ship superstructure, i.e. ramp, notch and flap, in different Wind-Over-Deck (WOD) conditions are discussed. From the steady simulation results, the effect of spatial variation of ship airwake on rotor airloads is concluded. The aerodynamic modifications reduce the strength of shedding vortex and increase rotor normal force through delaying and relieving flow separation, and therefore are beneficial to alleviate the limitation of control inputs. By contrast, the perturbation of unsteady ship airwake can cause the serious oscillation of rotor forces during shipboard landing. The unsteady simulations show that the turbulence intensity of ship airwake and oscillatory rotor airloading, represented by Root-Mean-Square (RMS) loading, can be remarkably reduced by the ramp and notch modifications, while the flap modification has adverse effect. It means that flow control devices have large potential benefits to alleviate the pilot’s workload and improve the shipboard landing safety, but they should be well designed to avoid the introduction of more vortex, which leads to increase in disturbance of flow field.     

Robustness evaluation method for unmanned aerial vehicle swarms based on complex network theory

Unmanned Aerial Vehicle (UAV) swarms have been foreseen to play an important role in military applications in the future, wherein they will be frequently subjected to different disturbances and destructions such as attacks and equipment faults. Therefore, a sophisticated robustness evaluation mechanism is of considerable importance for the reliable functioning of the UAV swarms. However, their complex characteristics and irregular dynamic evolution make them extremely challenging and uncertain to evaluate the robustness of such a system. In this paper, a complex network theory-based robustness evaluation method for a UAV swarming system is proposed. This method takes into account the dynamic evolution of UAV swarms, including dynamic reconfiguration and information correlation. The paper analyzes and models the aforementioned dynamic evolution and establishes a comprehensive robustness metric and two evaluation strategies. The robustness evaluation method and algorithms considering dynamic reconfiguration and information correlation are developed. Finally, the validity of the proposed method is verified by conducting a case study analysis. The results can further provide some guidance and reference for the robust design, mission planning and decision-making of UAV swarms.     

An aggregate flow based scheduler in multi-task cooperated UAVs network

Unmanned Aerial Vehicles (UAVs) cooperative multi-task system has become the research focus in recent years. However, the existing network frameworks of UAVs are not flexible and efficient enough to deal with the complex multi-task scheduling, because they are not able to perceive the different features. In this paper, a novel cooperated UAVs network framework for multi-task scheduling is proposed. It is a three-layer network including a core layer, an aggregation layer and an execution layer, which enhances the efficiency of multi-task distribution, aggregation and transmission. Furthermore, an AggreGate Flow (AGFlow) based scheduler is dedicatedly designed to maximize the task completion rate, whose key point is to aggregate flows belonging to one task during the multi-task transmission of UAVs network and to allocate priority by calculating the urgency-level of each AGFlow. Simulation results demonstrate that, compared with that of state-of-the-art scheduler, the average task completion rate of AGFlow based scheduler is raised by 0.278.     

无人船数据链SC-FDE突发信号载波同步方法

设计了一种适用于无人船组网数据链的SC-FDE突发通信时隙的帧结构,通过计算前导序列和独特字(UW)序列的自相关函数,调整差分相关长度,提出一种适用于多模式帧结构的载波同步方法。最后,通过仿真评估了所提出算法在不同条件下的有效频偏估计范围、频偏估计精度等性能,为算法工程实现的主要设计参数提供参考。     

Virtual target guidance-based distributed model predictive control for formation control of multiple UAVs

The paper proposes a Virtual Target Guidance (VTG)-based distributed Model Predictive Control (MPC) scheme for formation control of multiple Unmanned Aerial Vehicles (UAVs). First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem (FHOCP) can be solved by swarm intelligent optimization algorithm. Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance. Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function. Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.     

A multi-criteria fusion feature selection algorithm for fault diagnosis of helicopter planetary gear train

Planetary gear train is a prominent component of helicopter transmission system and its health is of great significance for the flight safety of the helicopter. During health condition monitoring, the selection of a fault sensitive feature subset is meaningful for fault diagnosis of helicopter planetary gear train. According to actual situation, this paper proposed a multi-criteria fusion feature selection algorithm (MCFFSA) to identify an optimal feature subset from the high-dimensional original feature space. In MCFFSA, a fault feature set of multiple domains, including time domain, frequency domain and wavelet domain, is first extracted from the raw vibration dataset. Four targeted criteria are then fused by multi-objective evolutionary algorithm based on decomposition (MOEA/D) to find Proto-efficient subsets, wherein two criteria for measuring diagnostic performance are assessed by sparse Bayesian extreme learning machine (SBELM). Further, F-measure is adopted to identify the optimal feature subset, which was employed for subsequent fault diagnosis. The effectiveness of MCFFSA is validated through six fault recognition datasets from a real helicopter transmission platform. The experimental results illustrate the superiority of combination of MOEA/D and SBELM in MCFFSA, and comparative analysis demonstrates that the optimal feature subset provided by MCFFSA can achieve a better diagnosis performance than other algorithms.     

General optimal design of solar-powered unmanned aerial vehicle for priority considering propulsion system

This paper describes the general optimization design method of Solar-Powered Unmanned Aerial Vehicle which priority considering propulsion system planning. Based on the traditional solar powered aircraft design method, the propulsion system top-level target parameters which affect the path planning are integrated into the general optimization design. According to the typical mission requirements of Solar-Powered Unmanned Aerial Vehicle, considering the design variables such as wing area, aspect ratio, design mission date and so on, the general optimization is carried out with the minimum aircraft weight as the optimization objective. The influence of wing area and aspect ratio on the optimal design results is analyzed and compared with the traditional design method. The results show that the general design method of Solar-Powered Unmanned Aerial Vehicle for priority considering propulsion system can greatly reduce the electricity demand of energy storage battery, greatly reduce the aircraft weight of Solar-Powered Unmanned Aerial Vehicle.     

Command filtered sliding mode trajectory tracking control for unmanned airships based on RBFNN approximation

This paper presents two sliding mode controllers to address the trajectory tracking problem of unmanned airships in the presence of unknown wind disturbance. The sliding mode controller proposed first is designed by a fast power rate reaching law(FPRRL). The disturbance is compensated by a radial basis function neural network (RBFNN). To avoid the aggressive adaptation, the controller is augmented by a command filter. The controller provides good robustness and tracking performance with no chattering under the hypothesis of ideal wind field. However, serious chattering occurs when simulation is performed under discontinuous wind field. To simulate the wind in practice, the wind field employed in the simulation is generated by the combination of a constant field and white noise. The controller is improved subsequently with an extended model to suppress the chattering induced by the white noise. The enhanced controller manipulates the derivation of system input, thus attenuating the chattering. Stability analysis shows that both controllers drive the tracking error into a controllable small region near zero. Simulations are provided to validate the performance of the proposed controllers under different wind hypothesis.     

用EXCEL—VB建立一个实用的程序库

本文介绍了一个以EXECL和EXCEL VB建立的直升机实用程序库及其建立和使用方法。