Multi-state autonomous drilling for lunar exploration

Due to the lack of information of subsurface lunar regolith stratification which varies along depth, the drilling device may encounter lunar soil and lunar rock randomly in the drilling process. To meet the load safety requirements of unmanned sampling mission under limited orbital resources, the control strategy of autonomous drilling should adapt to the indeterminable lunar environments. Based on the analysis of two types of typical drilling media (i.e., lunar soil and lunar rock), this paper proposes a multi-state control strategy for autonomous lunar drilling. To represent the working circumstances in the lunar subsurface and reduce the complexity of the control algo-rithm, lunar drilling process was categorized into three drilling states:the interface detection, initi-ation of drilling parameters for recognition and drilling medium recognition. Support vector machine (SVM) and continuous wavelet transform were employed for the online recognition of dril-ling media and interface, respectively. Finite state machine was utilized to control the transition among different drilling states. To verify the effectiveness of the multi-state control strategy, drilling experiments were implemented with multi-layered drilling media constructed by lunar soil simulant and lunar rock simulant. The results reveal that the multi-state control method is capable of detect-ing drilling state variation and adjusting drilling parameters timely under vibration interferences. The multi-state control method provides a feasible reference for the control of extraterrestrial autonomous drilling.     

Motion synchronization in a dual redundant HA/EHA system by using a hybrid integrated intelligent control design

This paper presents an integrated fuzzy controller design approach to synchronize a dis-similar redundant actuation system of a hydraulic actuator (HA) and an electro-hydrostatic actu-ator (EHA) with system uncertainties and disturbances. The motion synchronous control system consists of a trajectory generator, an individual position controller for each actuator, and a fuzzy force tracking controller (FFTC) for both actuators. The trajectory generator provides the desired motion dynamics and designing parameters of the trajectory which are taken according to the dynamic characteristics of the EHA. The position controller consists of a feed-forward controller and a fuzzy position tracking controller (FPTC) and acts as a decoupled controller, improving posi-tion tracking performance with the help of the feed-forward controller and the FPTC. The FFTC acts as a coupled controller and takes into account the inherent coupling effect. The simulation results show that the proposed controller not only eliminates initial force fighting by synchronizing the two actuators, but also improves disturbance rejection performance.     

某型直升机维修保障能力生成模式研究

某型直升机是陆航部队近年来新装备的主力作战机型,目前正处于装备部队初期的故障高发阶段,而部队有限的装备维修保障能力直接制约了该型机战斗力的形成。本文结合前期对某型直升机的自身技术特点及其装备维修保障的研究,综合使用单位反映的各种问题,深入剖析了制约其维修保障能力形成的原因,以期为后续新装备快速形成装备维修保障能力提供借鉴。     

基于ANFIS的智能导航自适应滤波算法研究

智能导弹等智能化飞行器在快速跨域、高速机动飞行时,由于传感器切换、外形改变等因素,会对组合导航信息融合系统引入随机非Gauss噪声等影响,离线优化的参数往往不能满足滤波器精度的需求。自适应网络模糊推理系统ANFIS是一种将人工神经网络和模糊推理技术相结合而成,符合人类认知特点的决策方法,它可以对导航数据进行学习,实现智能决策、实时修改滤波器内部参数,对滤波器进行优化。仿真结果表明,基于ANFIS优化的智能导航自适应滤波算法可以有效减少噪声和干扰带来的影响,提高导航精度。     

基于小波变换和支持向量机的开关电流电路故障诊断新方法

针对开关电流(Switched current,SI)电路的故障诊断和定位问题，为进一步提高故障诊断准 确率，提出了基于小波变换和粒子群优化(Particle swarm optimization，PSO)支持向量机 (Support vector machine，SVM)的开关电流电路故障诊断新方法。该方法首先对节点电流 信号进行蒙特卡罗分析，然后通过小波分解计算分形维数，再利用核主元分析（Kernel pri ncipal component analysis，KPCA）降低特征值维数，实现最优故障特征的提取。最后通 过PSO SVM完成对各种故障模式的分类。对六阶切比雪夫低通滤波器进行了仿真实验验证， 获取了较高的故障诊断准确率，与其他方法进行比较，实验结果显示了本文方法的优越性。     

抗离群值的鲁棒正则化贯序超限学习机

针对离群值环境下的在线学习问题,提出一种鲁棒正则化贯序超限学习机(Robust regularized online sequential extreme learning machine,RR-OSELM)。RR-OSELM以增量学习新样本的方式实现在线学习,并在学习过程中基于样本的先验误差进行逆向加权计算以降低学习模型对于离群值的敏感性;同时RR-OSELM通过融合使用Tikhonov正则化技术进一步增强了其在实际应用中的稳定性。实验结果表明,RR-OSELM具有较同类算法更好的鲁棒性和实用性,对于离群值环境下的在线建模与预测问题是积极有效的。     

Behavior and functional modeling methods of doubly salient electromagnetic generators for aircraft electrical power system applications

The Doubly Salient Electromagnetic Generator(DSEG) is a promising candidate in aircraft generator application due to the simplicity, robustness and reliability. However, the field windings and the armature windings are strongly coupled, which makes the inductance characteristics non-linear and too complex to model. The complex model with low precision also leads to difficulties in modeling and analysis of the entire aircraft Electrical Power System(EPS). A behavior level modeling method based on modified inductance Support Vector Machine(SVM) is proposed. The Finite Element Analysis(FEA) inductance data are modified based on the experiment results to improve the precision. A functional level modeling method based on input–output characteristics SVM is also proposed. The two modeling methods are applied to a 9 kW DSEG prototype. The steady state and transient process precision of the proposed methods are proved by comparing with the experiment results. Meanwhile, the modeling time consumption, the application time consumption and the calculation resource demand are compared. The DSEG behavior and functional modeling methods provide precious results with high efficiency, which accelerates theoretical analysis and expands the application foreground of the DSEG in the aircraft EPS.     

基于欠采样的零阶优化算法

非平衡学习吸引了许多研究者的关注。一般情况下,少数类是更值得关注的,并且其误分类代价要远高于多数类。由于非平衡数据分布的非均衡性,标准的分类算法将难以适用。为了解决非平衡数据分类问题,给出了基于欠采样的零阶优化算法。首先,为了降低数据非平衡分布的影响,针对不同非平衡比的数据集给出了不同的两种采样策略。然后,采用了一种引入间隔均值项的支持向量机(Support vector machine,SVM)优化模型进行分类,并使用带有方差减小的零阶随机梯度下降算法进行求解,提高了算法的精度。在非平衡数据上进行了对比实验,实验证明提出的方法有效提高了非平衡数据的分类效果。     

气动钣金快速成形机的研制

针对电动钣金成形机制造成本高、效率低、易产生死点的问题,提出一种采用气液增力装置代替液压传动系统的气动钣金成形机设计方案。气液增力装置采用精密气压转换阀控制,实现行程平稳控制和加工成形过程平稳加载,显著提高了生产效率;配套研制的多种无齿收缩成形模具,可加工不同形状钣金件并获得更好的表面质量。该技术在钣金快速成形方面的研究处于国内领先水平,已获得3项国家专利。     

磁强计数据辨识卫星自旋状态

针对近地低轨三轴稳定卫星在轨管理后期,除磁强计外其他姿态敏感器都无效情况下的姿态异常问题,分析了三轴稳定卫星失去姿态基准后,星体自旋状态下三轴磁强计测量数据的特点,提出了使用磁强计测量数据的矢量信息,以找到能够获取卫星状态的方法,从而建立了磁强计测量矢量与卫星自旋轴的几何关系,给出了处于自旋状态下的卫星自旋轴确定方法。通过此种辨识方法,获得了某气象卫星姿态异常翻转状态下的自旋矢量方向和自旋角速度,从而证明了该辨识方法快速、有效,可以作为姿态异常卫星自旋状态的辨识手段,为恢复卫星姿态提供了重要信息,具有一定的工程应用价值。