蜂窝夹层板超高速撞击极限方程分析

为分析撞击极限方程对蜂窝夹层结构的穿透特性的预测能力,调研得到了3类撞击极限方程的表达形式和等效方法,以及131个采用碳纤维复合材料(CFRP)面板的蜂窝夹层板结构的试验数据,并对撞击极限方程的预测能力进行了比较计算。结果发现,MET方程对他源数据的四种(未失效、失效、总体以及安全)预测率均大于80%,进行在轨航天器结构的失效分析时可优先选用;SRL方程对本源数据的安全预测率达到了100%,在他源数据上的安全预测率也很高,适用于航天器防护结构设计。探讨了撞击极限方程中的系数、速度分界值的优化思路,以提高撞击极限方程的预测率。     

无人机用燃料电池阴极供气系统建模与控制

燃料电池因其高效、无污染、噪声小等特点,被认为是未来最具有潜力的无人机（UAV）用动力源,燃料电池阴极供气系统的控制技术是决定燃料电池系统性能和可靠性的关键。针对无人机用质子交换膜燃料电池（PEMFC）阴极供气系统,首先,考虑外界温度、压力、空气密度以及雷诺数等随高度变化的参数,建立了跨高度离心空压机模型并分析了其在不同高度下的工作特性,基于无刷直流电机反电势特征构建了高速空压机驱动电机模型。其次,通过计算燃料电池阴极氧气和氮气的动态分压获取了PEMFC电堆输出电压。设计了基于分数阶PI^λD^μ的过氧比和阴极气压控制方法,驱动电机采用有限集模型预测控制（MPC）实现快速的转矩响应,仿真结果表明设计的控制器可在无人机跨高度运行条件下实现过氧比的快速调节,同时维持阴极气压稳定,满足燃料电池阴极供气需求。     

对双基地雷达的间歇采样转发干扰效果分析

针对采用线性调频信号的双基地雷达,推导了间歇采样转发干扰数学模型.详细分析了干扰过程中雷达距离分辨力变化的影响,以及对干扰机的功率需求.仿真结果表明,间歇采样转发干扰可以产生前移的假目标,其前移距离远大于双基地雷达接收视线上的距离分辨力;通过选择合适的干扰功率,可以使得假目标幅度不小于真实目标幅度,达到有效的前移假目标...     

Multi-UAV coordination control by chaotic grey wolf optimization based distributed MPC with event-triggered strategy

The paper proposes a new swarm intelligence-based distributed Model Predictive Control (MPC) approach for coordination control of multiple Unmanned Aerial Vehicles (UAVs). First, a distributed MPC framework is designed and each member only shares the information with neighbors. The Chaotic Grey Wolf Optimization (CGWO) method is developed on the basis of chaotic initialization and chaotic search to solve the local Finite Horizon Optimal Control Problem (FHOCP). Then, the distributed cost function is designed and integrated into each FHOCP to achieve multi-UAV formation control and trajectory tracking with no-fly zone constraint. Further, an event-triggered strategy is proposed to reduce the computational burden for the distributed MPC approach, which considers the predicted state errors and the convergence of cost function. Simulation results show that the CGWO-based distributed MPC approach is more computationally efficient to achieve multi-UAV coordination control than traditional method.     

Aircraft air conditioning system health state estimation and prediction for predictive maintenance

The vast potential of system health monitoring and condition based maintenance on modern commercial aircraft is being realized through the innovative use of Airplane Condition Monitoring System (ACMS) data. However there are few methods addressing the issues of failure prognostics and predictive maintenance for commercial aircraft Air Conditioning System (ACS). This study developed a Bayesian failure prognostics approach using ACMS data for predictive maintenance of ACS. First, a health index characterizing the ACS health state is inferred from a multiple sensor signals using a data driven method. Then a dynamic linear model is proposed to describe the degradation process for failure prognostics. Bayesian inference formulas are carried out for degradation estimation and prediction. The developed approach is applied on a passenger aircraft fleet with ACMS data recorded for one year. The analysis of the case study shows that the developed method can produce satisfactory prognostics results, where all the ACS failure precursors are identified in advance, and the relative errors for the failure time prediction made when just entering the degradation warning stage are less than 8%. This would allow operators to proactively plan future maintenance.     

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.     

基于滑模干扰观测器的空空导弹三维预测制导律设计

针对目标大机动情况下制导准确性较差的问题,研究了基于滑模干扰观测器的空空导弹三维预测制导律。利用连续时间非线性预测控制方法,根据导弹当前的状态,选择弹道跟踪误差作为预测性能指标,对其进行在线滚动优化,获得制导指令。同时为了进一步提高导弹制导规律的抗干扰能力,利用滑模干扰观测器对内部不确定性和外部未知干扰进行逼近,并与预测控制方法所得到的制导指令进行综合得到优化制导指令。最后仿真结果表明,所设计的PCG相比于传统的PN,性能有较大的改善,能够实现目标大机动情况下的精确制导,并且所需导弹机动过载小、脱靶量小,具有一定的鲁棒性。     

电液仿真转台控制系统设计与仿真研究

针对影响三轴电液仿真转台动、静态性能最大的同步驱动、摩擦和大惯量负载干扰三个问题，采用了模拟人脑基于经验控制的FNN（模糊神经网络）控制器和基于学习校正的PNN（预测神经网络）控制器分别对应转台内环（角速度环）和外环（角度环）反馈系统。FNN同步控制器分为等同和主从同步控制模式，两种模式相互切换，提高了系统同步性能；PNN摩擦干扰控制器采用了基于双网络模型的NARMA（非线性自回归滑动平均）预测模型，具有较强的非线性系统辨识能力，提高了系统抗干扰能力。软件仿真结果表明，当转台外框负载发生变化或外框两马达转速相差较大时，使用PNN—FNN模型的智能控制系统仍具有较高的位置跟踪精度和动态性能。     

地形跟随系统的并行预测控制方法

本文基于脉动（Ｓｙｓｔｏｌｉｃ）阵列结构，提出了一种基于状态空间模型预测控制的并行算法，这种算法可以通过阵列结构并行实现，以满足地形跟随系统的实时控制参数合成的要求     

Trajectory tracking control of a VTOL unmanned aerial vehicle using offset-free tracking MPC

Designing a stable and robust flight control system for an Unmanned Aerial Vehicle (UAV) is an arduous task. This paper addresses the trajectory tracking control problem of a Ducted Fan UAV (DFUAV) using offset-free Model Predictive Control (MPC) technique in the presence of various uncertainties and external disturbances. The designed strategy aims to ensure adequate flight robustness and stability while overcoming the effects of time delays, parametric uncertainties, and disturbances. The six degrees of freedom DFUAV model is divided into three flight modes based on its airspeed, namely the hover, transition, and cruise mode. The Dryden wind turbulence is applied to the DFUAV in the linear and angular velocity component. Moreover, different uncertainties such as parametric, time delays in state and input, are introduced in translational and rotational components. From the previous work, the Linear Quadratic Tracker with Integrator (LQTI) is used for comparison to corroborate the performance of the designed controller. Simulations are computed to investigate the control performance for the aforementioned modes and different flight phases including the autonomous flight to validate the performance of the designed strategy. Finally, discussions are provided to demonstrate the effectiveness of the given methodology.