Reconfigurable fault-tolerant control for supersonic missiles with actuator failures under actuation redundancy

Aircraft undergoing actuator failures into under-actuation have been seldom studied in literature. Aiming at addressing actuator failures of Total Loss of Effectiveness (TLOE) as well as Partial Loss of Effectiveness (PLOE) resulting in different system actuations, reconfigurable Fault-Tolerant Control (FTC) is proposed for supersonic wingless missiles under actuation redundancy. The under-actuated system of TLOE failure patterns is solved by transformation to cascade systems through a ‘shape variable’. Meanwhile, actuator TLOE faults of different unknown failure patterns from proper actuation to under-actuation are accommodated by a reconfigurable adaptive law on a multiple-model basis. The backstepping technique with the Extended State Observer (ESO) method adopted as a basic strategy is applied to an established symmetric coupled missile system with actuator PLOE faults, modeling errors, and external disturbances. Additionally, the nonlinear saturation characteristics of actuators are settled by an auxiliary system with the Nussbaum function technique. The stability of the control system is analyzed and proven through Lyapunov theory. Numerical simulations are implemented in the presences of aerodynamic uncertainties, gust disturbance, and actuator failures. Results demonstrate the effectiveness of the proposed method with satisfactory tracking performance and actuator fault tolerance capacity.     

基于改进FCM的北斗三频组合观测值选取

以北斗卫星导航系统三频双差为基础探讨了组合观测值及误差,针对以往采用聚类方法在研究GPS三频组合数据过程中的不足,提出了基于距离修正的增量模糊C均值算法.通过调节因子有效地修正了样本中心与聚类中心的距离,获得合理的隶属度,从而得到正确的分类;构造了基于距离修正的聚类有效性指标,自动获取最佳聚类数,避免了人为确定聚类数的不合理性;在此基础上引入增量的思想,数据增加时以原有的数据集为基础,根据阈值进行归类,不需要重新进行初始计算.通过矩阵变换法及实例验证了该方法的可行性和可靠性.     

Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.     

基于位移和力值组合的静重式力标准机砝码加卸载控制方法研究

介绍了一种基于位移和力值组合的静重式力标准机砝码加卸载的控制方法，通过监测砝码的移动量和参考力传感器叠加系统的力值量，实时调整加卸载机构的加卸载速度，以实现对被检力传感器的平滑加卸载的目的。该方法有效解决了吊挂在加载过程中产生较大摆动，影响力标准机复现力值准确度的问题，同时也消除了力值过冲现象，避免了因逆程效应而导致的力传感器输出偏差。     

Neural network-based fault diagnosis for spacecraft with single-gimbal control moment gyros

This paper proposes a neural network-based fault diagnosis scheme to address the problem of fault isolation and estimation for the Single-Gimbal Control Moment Gyroscopes(SGCMGs) of spacecraft in a periodic orbit. To this end, a disturbance observer based on neural network is developed for active anti-disturbance, so as to improve the accuracy of fault diagnosis.The periodic disturbance on orbit can be decoupled with fault by resorting to the fitting and memory ability of neural network. Subsequ...     

航空发动机两种加速控制计划的融合控制方法研究

转速导数(N-dot)和换算燃油流量加速控制计划是航空发动机加速过程安全、快速的重要保障,但各自分别易受到功率提取、性能衰退和传感器、燃油计量装置误差的影响导致失速喘振或加速性的下降。为了提高所控制加速过程的鲁棒性,使用这两种控制计划所获燃油流量的偏差大小对N-dot控制计划的控制目标进行调节修正的融合控制方法获得实际的加速燃油流量。以双转子加力涡扇发动机为对象的仿真验证表明,该控制方法可以适应全包线加速控制的需要;相比其余两种控制计划在受功率提取、误差影响下保持正常工作的范围更广;相同工作条件下,该方法比N-dot控制计划更不易发生喘振,比换算燃油流量控制计划的加速时间更小。     

基于控制分配的恒压腔压力精准控制

针对采用双阀调节的恒压腔系统压力在空气流量大范围变化时的精确控制问题,提出了一种基于控制分配的恒压腔压力精准控制方法。首先,建立了虚拟放气流量的双阀控制分配算法,包括：建立满足虚拟放气流量要求且调节阀能耗最小的优化问题;通过线性矩阵不等式(Linear Matrix Inequality, LMI)求解该优化问题得到双阀实际流通面积值;考虑调节阀动态并计算调节阀控制信号指令值。其次,建立以虚拟放气流量为恒压腔控制输入的闭环负反馈回路,基于此,设计满足伺服性能和抗干扰性能要求的PI控制器,引入上述双阀控制分配算法,进而构建完整的基于控制分配的恒压腔压力控制系统。仿真结果表明,采用该方法的控制系统性能明显优于传统单阀PI控制系统性能,恒压腔压力动态相对误差小于0.07%;干扰流量最大变化率为77kg/s2时,压力最大偏差低于500Pa;此外,调节阀动态时间常数和流量系数的拉偏仿真结果进一步验证了该控制器的鲁棒性。     

基于PID和LESO的无人机控制

针对四旋翼无人机控制模型耦合程度高、非线性关系复杂,设计了一种基于PID和LESO的控制方法,选取无人机的某个状态变量作为控制量,通过简化模型对状态变量进行解耦控制,进而在控制系统中加入线性扩张状态观测器(LESO),提高模型的抗干扰能力。通过仿真和实际飞行与传统PID方法进行比较,充分验证了自抗扰控制(ADRC)在无人机飞行控制中具有鲁棒性强、精度高、易于实现等特点。     

基于FQFD的太阳能无人机设计指标排序方法

为解决太阳能无人机（UAV）总体设计中任务需求表达模糊、技术指标重要度排序决策困难的问题,提出了基于模糊质量功能展开（FQFD）的太阳能无人机总体设计指标排序方法。该方法在传统质量功能展开（QFD）质量屋的基础上,引入三角模糊数,表征任务需求的不确定性和模糊性;在模糊隶属度函数未知的情况下,采用α加权修正水平截集去模糊化方法计算技术指标重要度,获得技术指标重要度排序,为总体设计优化决策提供依据。最后以长航时太阳能无人机的总体设计为例,对任务需求—工程特性—技术指标的两级质量屋模型进行计算分析,得到续航能力、巡航高度、动力系统效率、巡航速度和气动效率是太阳能无人机最重要的5个技术指标的结果。此方法客观性较强,可处理复杂的系统不确定性,为太阳能无人机总体方案设计及决策应用提供参考依据。     

Civil unmanned aircraft system operation in national airspace: A survey from Air Navigation Service Provider perspective

Unmanned Aircraft Systems (UASs) have advanced technologically and surged exponentially over recent years. Currently, due to safety concerns, most civil operations of UAS are conducted in low-level uncontrolled area or in segregated controlled airspace. As the industry progresses, both operational and technological capabilities have matured to the point where UASs are expected to gain greater freedom of access to both controlled and uncontrolled airspace. Extensive technical and regulatory surveys have been conducted to enable the expanded operations. However, most surveys are derived from the perspective of UAS own operating mechanism and barely consider interactions of their non-segregated activities with the Air Traffic Management (ATM) system. Hence, to fill the gap, this paper presents a survey conducted from the perspective of Air Navigation Service Provider (ANSP), which serves to accommodate these new entrants to the overall national airspace while continuing flight safety and efficiency. The primary objectives of this paper are to: (A) describe what typical ANSP-supplied UAS Traffic Management (UTM) architecture is required to facilitate all types of civil UAS operations; (B) identify three major ANSP considerations on how UAS can be accommodated safely in civil airspace; (C) outline future directions and challenges related with UAS operations for the ANSP.