Grain erosion wear properties and grinding performance of porous aggregated cubic boron nitride abrasive wheels

Cubic boron nitride (cBN) superabrasive grinding wheels exhibit unique advantages in the grinding of difficult-to-cut materials with high strength and toughness, such as titanium alloys and superalloys. However, grinding with multilayered metallic cBN superabrasive wheels faces problems in terms of grain wear resistance, the chip storage capability of the working layers and the stability and controllability of the dressing process. Therefore, in this work, novel metallic cBN superabrasive wheels with aggregated cBN (AcBN) grains and open pore structures were fabricated to improve machining efficiency and surface quality. Prior to the grinding trials, the air-borne abrasive blasting process was conducted and the abrasive blasting parameters were optimized in view of wear properties of cBN grains and metallic matrix materials. Subsequently, the comparative experiments were performed and then the variations in grinding force and force ratio, grinding temperature, tool wear morphology and ground surface quality of the multilayered AcBN grinding wheels were investigated during machining Ti–6Al–4V alloys. In consideration of the variations of grain erosion wear volume and material removal rate per unit of pure metallic matrix materials as the abrasive blasting parameters changes, the optimal abrasive blasting parameters were identified as the SiC abrasive mesh size of 60# and the abrasive blasting distance and time of 60 mm and 15 s, respectively. The as-developed AcBN grains exhibited better fracture toughness and impact resistance than monocrystalline cBN (McBN) grains because of the existence of metal-bonded materials amongst multiple cBN particles that decreased crack propagation inside whole grains. The metallic porous AcBN wheels had lower grinding forces and temperature and better ground surface quality than vitrified McBN wheels due to the constant layer-by-layer exposure of cBN particles in the working layer of AcBN wheels.     

Fractional order adaptive robust formation control of multiple quad-rotor UAVs with parametric uncertainties and wind disturbances

In recent times, multiple Unmanned Aerial Vehicles (UAVs) are being widely utilized in several areas of applications such as agriculture, surveillance, disaster management, search and rescue operations. Degree of robustness of applied control schemes determines how accurate a swarm of UAVs accomplish group tasks. Formation and trajectory tracking controllers are required for the swarm of multiple UAVs. Factors like external environmental effects, parametric uncertainties and wind gusts make the controller design process as a challenging task. This article proposes fractional order formation and trajectory tacking controllers for multiple quad-rotors using Super Twisting Sliding Mode Control (STSMC) technique. To compensate the effects of the disturbances due to parametric uncertainties and wind gusts, Lyapunov function based adaptive controllers are formulated. Moreover, Lyapunov theorem is used to guarantee the stability of the proposed controllers. Three types of controllers, namely fixed gain STSMC and fractional order Adaptive Super Twisting Sliding Mode Control (ASTSMC) methods are tested for the swarm of UAVs by performing the numerical simulations in MATLAB/Simulink environment. From the presented results, it is verified that in presence of wind disturbances and parametric uncertainties, the proposed fractional order ASTSMC technique showed improved robustness as compared to the fixed gain STSMC and integer order ASTSMC.     

Robust optimal sliding mode control for the deployment of Coulomb spacecraft formation flying

Inter-spacecraft electrostatic force (Coulomb force) is desirable for close formation flying control because of its propellant-less and free contaminate characteristics attributed to the propellant exhaust emission. This paper presents robust optimal sliding mode control to deal with the problem of thruster saturation in tracking the formation trajectory for Coulomb spacecraft formation flying. The robust controller design is based on optimal control theory as a linear quadratic system, and it is augmented with an integral sliding mode control technique. The stability of the closed-loop system is guaranteed using the second Lyapunov method. The developed controller outperforms the existing ones, because it has a higher degree of fine-tuning to cope with the uncertainty. Numerical simulations are employed to confirm the efficiency of the developed controller.     

增强神经网络辨识模型泛化能力的研究

神经网络(Artificial Neural Network,ANN)辨识模型的泛化能力是其最主要的性能之一,增强ANN模型的泛化能力也是近年来国内外有关专家学者研究的重点问题。大量研究表明,ANN模型泛化能力的改善与很多因素相关联,其中恰当的性能指标函数设计是一个重要影响因素。文中在分析常见的基于均方误差最小原则的性能指标函数基础上,通过加入ANN辨识模型权值间的延迟信息,进而获得一种改进型性能指标函数。通过仿真,验证了所设计的改进型性能指标函数对增强ANN辨识模型的泛化能力是有效的。     

“田园一号”微推进系统设计与性能测试

针对“田园一号”微纳星编队飞行任务的技术需求，开展了微推进系统的总体设计。常规冷气推进由于其比冲低、贮存压力高、结构复杂，难以满足微纳卫星需求。选择R134a作为推进工质，通过将推进剂液化，减小系统体积。基于3D打印技术，设计贮箱、稳压罐、管路一体的推进系统。采用MEMS加工工艺，设计并研制出电加热喷口，从而提高系统比冲。分析了不同喷口尺寸、供气压力以及温度下所产生的推力和比冲大小，确定出喷口设计。表征测试所研制的电加热喷口，结果表明喷口加工误差控制在2%以内。真空条件下，采用扭摆测量系统测试推力器推进性能，测试结果表明，当稳压罐内气体压力在0.1～0.2 MPa变化时，推力大小为5～10 mN。当喷气温度从25℃升至95℃时，推进系统比冲可提升10%以上。