基于自适应模糊滑模控制的机器人轨迹跟踪算法

针对控制参数的不确定性以及存在未知外部扰动情况下移动机器人的轨迹跟踪问题,提出一种基于光滑非线性饱和函数的自适应模糊滑模轨迹跟踪控制算法。通过建立不确定非线性移动机器人运动控制模型,利用自适应模糊逻辑系统构建自适应模糊滑模控制器。为了增强轨迹跟踪控制算法对随机不确定外部扰动适应能力的同时削弱滑模控制算法中的输入抖振现象,利用有界输入有界输出(BIBO)稳定的方法,通过带有自适应调节算法的模糊系统对滑模控制律中非线性函数项进行自适应逼近,并设计了模糊系统中可调参数的自适应控制律,保证了控制系统的稳定与收敛。实验结果表明,所设计的控制器对系统参数不确定性和外界扰动均具有较强的轨迹跟踪性能和鲁棒性。与传统的滑模控制算法相比,该算法不仅能有效减小输入抖振而且轨迹跟踪控制精度提高了18.89%。     

航空器轨迹冲突探测方法的改进与仿真

针对传统轨迹冲突探测方法忽略航空器外形轮廓会造成空域浪费的问题,对冲突探测几何近似法进行改进.考虑航空器外形尺寸对轨迹冲突探测结果的影响,提出扩展保护区的概念,给出相应几何近似法的计算步骤,并通过仿真实验对所提出的几何近似法的有效性进行验证.仿真实验表明:所提出的几何近似法的结果能反映轨迹冲突概率的变化趋势,更接近冲突概率的真实情况.     

FRP加固局部损伤钢压杆的稳定分析

钢结构中存在大量的轴心受力构件,作为承受永久竖向荷载的主要构件,往往是结构加固的重点.采用能量方法,分析各种杆端约束条件下,纤维增强复合材料（FRP）加固局部损伤的轴心受压钢构件在弹性失稳时的弹性屈曲临界力,并建立普遍适用的近似欧拉公式.利用ANSYS通用有限元分析软件分析FRP的厚度对损伤空心圆管临界力的影响并与该公式解析解进行对比.计算结果表明,该公式计算结果可靠,采用纤维增强复合材料加固修复局部损伤的钢结构可以有效恢复其刚度和稳定性.     

新疆西准噶尔哈图岩体地球化学特征及其地质意义

哈图岩体侵位于西准噶尔南部早—中泥盆世海相火山-沉积地层中,主要岩性为二长花岗岩、正长花岗岩及少量碱长花岗岩,是研究西准噶尔晚石炭世构造环境的理想对象。哈图岩体花岗岩中SiO₂含量(质量分数,下同)为72.06%～76.53%,全碱(Na₂O+K₂O)为7.80%～8.57%,CaO为0.20%～1.58%,MgO为0.07%～0.42%,明显具有高Si、富碱、贫Ca、低Mg的特征; 这些花岗岩的Al₂O₃含量为12.55%～14.06%,A/CNK值为1.06～1.15,A/NK值为1.15～1.36,显示其为弱过铝质—强过铝质花岗岩。此外,哈图岩体具有较低的稀土元素总含量((88.14～139.53)×10^-6)和高的轻、重稀土元素比值((La/Yb)_N值为3.04～6.50),在球粒陨石标准化稀土元素配分模式中显示为典型的右倾“V”字形且具有强烈的负Eu异常,表明源区可能有斜长石残留或出现斜长石的分离结晶作用; 在原始地幔标准化微量元素蛛网图中,这些花岗岩明显富集Rb、Th、U、K、Pb等大离子亲石元素,相对富集Zr、Hf,强烈亏损Sr、Ti、P,相对亏损Ba、Nb。以上特征及主量、微量元素特征和图解表明,哈图岩体为典型的弱过铝质—强过铝质A₂型花岗岩,其形成于造山后伸展阶段,是由洋壳和岛弧组成的新生地壳受上涌的幔源物质加热,在浅部低压条件下发生部分熔融,再经分离结晶作用的产物。     

影响弹丸起始扰动的火炮结构参数灵敏度分析与优化研究

弹丸起始扰动对火炮射击精度有重要影响,为了减小弹丸起始扰动,建立了某大口径轻型牵引炮弹炮耦合全炮动力学参数化有限元模型,由弹丸出炮口时刻弹丸的角位移、角速度表征弹丸起始扰动,构建优化目标函数,对火炮结构参数的影响程度进行灵敏度分析;同时利用径向基神经网络近似模型方法对弹丸起始扰动进行优化研究。结果表明,摇架臂板厚对弹丸起始扰动影响显著,优化后弹丸出炮口时刻弹丸角位移和角速度均明显减小。该结果可为火炮结构设计提供理论依据。     

高频辐射噪声近程传播特性研究

针对近程反鱼雷武器系统建设问题,研究了鱼雷高频辐射噪声的近场传播特性。采用小斜率近似（SSA）方法研究了粗糙海面的声散射特性,给出了具有高斯分布粗糙海面的2阶～4阶SSA双站散射系数计算公式,讨论了2阶SSA双站散射系数随海面粗糙度及入射角度不同的变化规律。并利用SSA双站散射系数计算了水下高频辐射噪声散射声场。仿真结果表明,粗糙海面的散射效应对高频辐射噪声传播产生较大影响,在研究声源/接收器位于近海面的高频辐射噪声传播特性时,应充分考虑海面的散射效应。本文的研究为分析浅海目标声散射特性时,是否需要考虑海面（海底）所引起的多途效应提供了理论依据。     

Ir-Rh合金力学性能的第一性原理计算

采用基于密度泛函理论的第一性原理分析方法,用虚拟晶格近似方法计算了Ir-x Rh (x=0、1、2、3、4、5、6、7、8、9、10、12、15、17、20、22、25、27、30)合金的晶格参数、体积模量、剪切模量、杨氏模量等力学参数。通过计算焓变值、电子态密度、能带结构从电子角度分析Rh掺杂对Ir-Rh合金力学性能的影响。结果表明：在Ir中掺杂少量Rh,能够提高材料的强度和硬度,在Ir-5Rh处达到顶点,之后随着Rh含量增加略有下降后继续升高,在Ir-10Rh处达到最大值,且数值与Ir-5Rh基本一致;随着Rh含量的增加,焓变值的绝对值由0.186 eV逐渐增加到0.634 eV,Ir-Rh合金热力学稳定性提高。另外,Ir-Rh合金的态密度、能带结构结果表明随着Rh含量的增加,键能升高,Ir-Rh合金脆性逐渐增大。     

Disjoint convex shell and its applications in mesh unfolding

In this work, we study a geometric structure called disjoint convex shell or simply DC-shell. A DC-shell of a polyhedron is a set of pairwise interior disjoint convex objects that collectively approximate the given polyhedron. Preventing convex objects from overlapping enables faster and robust collision response and more realistic fracturing simulation. Without the disjointness constraint, a physical realization of the approximation becomes impossible. This paper investigates multiple approaches that construct DC-shells from shapes that are either composed of overlapping components or segmented into parts. We show theoretically that, even under this rather simplified setting, constructing DC-shell is difficult.To demonstrate the power of DC-shell, we studied how DC-shell can be used in mesh unfolding, an important computational method in manufacturing 3D shape from the 2D material. Approximating a given polyhedron model by DC-shells provides two major benefits. First, they are much easier to unfold using the existing unfolding methods. Second, they can be folded easily by both human folder or self-folding machines. Consequently, DC-shell makes paper craft creation and design more accessible to younger children and provides chances to enrich their education experiences.     

Low-discrepancy sampling for approximate dynamic programming with local approximators

Approximate dynamic programming (ADP) relies, in the continuous-state case, on both a flexible class of models for the approximation of the value functions and a smart sampling of the state space for the numerical solution of the recursive Bellman equations. In this paper, low-discrepancy sequences, commonly employed for number-theoretic methods, are investigated as a sampling scheme in the ADP context when local models, such as the Nadaraya–Watson (NW) ones, are employed for the approximation of the value function. The analysis is carried out both from a theoretical and a practical point of view. In particular, it is shown that the combined use of low-discrepancy sequences and NW models enables the convergence of the ADP procedure. Then, the regular structure of the low-discrepancy sampling is exploited to derive a method for automatic selection of the bandwidth of NW models, which yields a significant saving in the computational effort with respect to the standard cross validation approach. Simulation results concerning an inventory management problem are presented to show the effectiveness of the proposed techniques.     

Heat effects due to mixing (dilution) the mixed acid solutions—Application of neural networks to approximate and generalize experimental data

The feed-forward neural networks have been used to approximate the specific molar enthalpy and the specific molar heat capacity of the mixed acid solutions. The nets have been trained with experimental data taken from the literature, so the values of the specific molar enthalpy and the specific molar heat capacity at the reference temperature T = 0 °C could be successively estimated for any composition of the mixed acid. Two principal methods have been considered and tested. In the first method two independent neural nets have been employed: the net NN-H, which approximates separately the specific molar enthalpy and the net NN-C, to approximate the specific molar heat capacity, respectively. In the second method only one net is employed (the net NN-HC), which simultaneously approximates both the specific molar enthalpy and the specific molar heat capacity. Then following both mentioned methods, the trained neural nets have been used to model the heat effects due to dilution of mixed acid solutions, carried out at various conditions – i.e. at any temperature and composition. Using these nets, both, the integral and the differential enthalpy balance can be carried out, so the smart and accurate method to model the mixed acid dilution has been elaborated. The proposed methods and their prediction accuracy have been successfully verified with our own experimental data carried out in the RC1 reaction calorimeter.