表面部分电极含金属芯压电纤维气流传感特性研究

含金属芯压电纤维可以模仿昆虫的毛发感受器,感知周围环境的气流变化。在含金属芯压电纤维的部分纵向表面涂镀电极,制备了表面部分电极含金属芯压电纤维传感器PMPF（Partial electrode of Metal core Piezoelectric Fiber）。基于平均电荷法,建立了悬臂梁结构PMPF准静态气流传感模型,分析了PMPF产生的电荷值与表面电极分布角度、纤维长度、气流流速和气流方向的关系。搭建了实验系统,测试了PMPF对冲击气流的响应,验证了理论模型。结果表明,PMPF的传感信号和气流流速成指数关系,和气流方向成“8”字形关系。PMPF具有气流速度和方向的传感性能。     

Composite adaptive dynamic surface control using online recorded data

This paper presents an online recorded data‐based design of composite adaptive dynamic surface control for a class of uncertain parameter strict‐feedback nonlinear systems, where both tracking errors and prediction errors are applied to update parametric estimates. Differing from the traditional composite adaptation that utilizes identification models and linear filters to generate filtered modeling errors as prediction errors, the proposed composite adaptation integrates closed‐loop tracking error equations in a moving time window to generate modified modeling errors as prediction errors. The time‐interval integral operation takes full advantage of online recorded data to improve parameter convergence such that the application of both identification models and linear filters is not necessary. Semiglobal practical asymptotic stability of the closed‐loop system is rigorously established by the time‐scales separation and Lyapunov synthesis. The major contribution of this study is that composite adaptation based on online recorded data is achieved at the presence of mismatched uncertainties. Simulation results have been provided to verify the effectiveness and superiority of this approach. Copyright © 2016 John Wiley & Sons, Ltd.     

A detection problem: Sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation

Sustainable management of groundwater-dependent vegetation (GDV) requires the accurate identification of GDVs, characterisation of their water use dynamics and an understanding of associated errors. This paper presents sensitivity and uncertainty analyses of one GDV mapping method which uses temperature differences between time-series of modelled and observed land surface temperature (LST) to detect groundwater use by vegetation in a subtropical woodland. Uncertainty in modelled LST was quantified using the Jacobian method with error variances obtained from literature. Groundwater use was inferred where modelled and observed LST were significantly different using a Student's t-test. Modelled LST was most sensitive to low-range wind speeds (<1.5 m s⁻¹), low-range vegetation height (<=0.5 m), and low-range leaf area index (<=0.5 m² m⁻²), limiting the detectability of groundwater use by vegetation under such conditions. The model-data approach was well-suited to detection of GDV because model-data errors were lowest for climatic conditions conducive to groundwater use.     

Robust Adaptive Neural Control for a Class of Time‐Varying Delay Systems with Backlash‐like Hysteresis Input

This paper proposes a robust adaptive dynamic surface control (DSC) scheme for a class of time‐varying delay systems with backlash‐like hysteresis input. The main features of the proposed DSC method are that 1) by using a transformation function, the prescribed transient performance of the tracking error can be guaranteed; 2) by estimating the norm of the unknown weighted vector of the neural network, the computational burden can be greatly reduced; 3) by using the DSC method, the explosion of complexity problem is eliminated. It is proved that the proposed scheme guarantees all the closed‐loop signals being uniformly ultimately bounded. The simulation results show the validity of the proposed control scheme.     

基于静力测试的三维曲面结构测点优化配置

传感器测点优化配置在结构健康监测系统中具有重要作用。针对结构健康监测中静力作用下三维曲面结构变形状况进行了研究,提出了三维曲面结构的测点优化配置方法。首先,对三维曲面结构进行测点组合选取,根据已知测点的响应值采用三维超曲面样条函数插值估计未布置测点的响应值,然后建立适应度函数,对未布置测点的估计值与实际值的误差进行判定,最后通过二重结构编码遗传算法对测点组合进行优化,选取适应度函数值最小的测点配置方案,从而实现了传感器测点优化配置的目的。应用该方法对简支的圆柱壳弯曲变形进行了测点优化配置,得到的适应度函数值最小的测点配置方案中,未布置测点的估计值与实际值的误差为1.10％,从而验证了该方法的可行性和有效性。     

基于熵和PSO优化SVM的肌电信号跌倒识别

跌倒对老年人的健康构成严重危害,设计了一种基于肌电信号的跌倒识别方法,可用于跌倒检测报警。该方法首先对表面肌电动作信号进行小波包分解,再依据信号特征选取信号的低频分量并重构,计算其排列组合熵,最后以4路肌电信号对应的排列组合熵组成的特征向量输入SVM进行模式识别并采用粒子群算法对SVM中惩罚参数c和核函数参数g进行优化,对8种动作进行识别实验,跌倒识别率88%,特异度98.3%,平均识别率97.0%,优于网格法和遗传算法支持向量机（GA-SVM）的参数优化,具有较强的鲁棒性和抗干扰能力。     

多无人艇联合攻击任务规划模型仿真

多水面无人舰艇之间的攻击任务规划是保证无人舰艇顺利高效完成攻击任务.多无人舰艇在执行联合攻击任务时,需要考虑到环境因素、不同任务的复杂度与各种复杂攻击任务执行能力等多方面的约束因素.传统的攻击任务调度模型在处理上述问题时,没有考虑攻击任务外界与内部的约束条件,只是将复杂的攻击任务简单地分解为个体的叠加,在任务执行过程中不仅达不到提高任务执行效率的目的,还会由于缺乏相应的协同规划机制陷入混乱状态.提出一种多无人艇联合攻击任务规划模型.根据水面无人舰艇集群攻击任务规划问题的多约束性,建立任务规划模型,引入代价函数,运用改进的生物地理粒子群优化算法对任务分配问题进行求解,避免了生物地理优化算法容易陷入局部最优和粒子群算法解多约束离散问题时的不稳定性.进行仿真的结果表明,所提出算法有效解决了多水面无人舰艇之间的攻击任务规划问题.     

多物理场耦合界面数据传递的仿真研究

高超声速飞行器的系统仿真是一个气动流场、结构应力场以及结构温度场的高度耦合过程,仿真过程中,需要在耦合界面上完成数据的迭代交换,传递的内容主要包括位移、速度、压力、温度等耦合数据,主要作用就是完成各个耦合场的方程之间参数的传递,在统一的仿真时间内实现仿真的迭代.耦合界面数据传递的技术难点在于要保证耦合界面处的总功守恒以及多物理场耦合仿真的精度[1].目前大多采用以插值为主的局部数据传递方法针对二元耦合开展研究与应用[1,3],局部插值的缺点在于全局精度偏低,偏差较大,计算速度不高.采用径向基函数法(RBF),对界面数据交换方法的仿真应用进行了研究,验证结果表明,计算精度满足仿真要求,求解方程的速度较快,工程应用效果较好.     

Adaptive output feedback tracking control of stochastic nonlinear systems with dynamic uncertainties

In this paper, adaptive output feedback tracking control is developed for a class of stochastic nonlinear systems with dynamic uncertainties and unmeasured states. Neural networks are used to approximate the unknown nonlinear functions. K‐filters are designed to estimate the unmeasured states. An available dynamic signal is introduced to dominate the unmodeled dynamics. By combining dynamic surface control technique with backstepping, the condition in which the approximation error is assumed to be bounded is avoided. Using It ô formula and Chebyshev's inequality, it is shown that all signals in the closed‐loop system are bounded in probability, and the error signals are semi‐globally uniformly ultimately bounded in mean square or the sense of four‐moment. Simulation results are provided to illustrate the effectiveness of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.     

A modified dynamic surface approach for control of nonlinear systems with unknown input dead zone

This paper focuses on the robust output precise tracking control problem of uncertain nonlinear systems in pure‐feedback form with unknown input dead zone. By designing an extended state observer, the states unmeasurable problem in traditional feedback control is solved, and the lumped uncertainty, which is caused by system unknown functions and input dead zone, is estimated. In order to apply separation principle, finite‐time extended state observer is designed to obtain system states and estimate the lumped uncertainty. Then, by introducing tracking differentiator, a modified dynamic surface control approach is developed to eliminate the ‘explosion of complexity’ problem and guarantee the tracking performance of system output. Because tracking differentiator is a fast precise signal filter, the closed‐loop control performance is significantly improved when it is used in dynamic surface control instead of first‐order filters. The L _∞ stability of the whole closed‐loop system, which guarantees both the transient and steady‐state performance, is shown by the Lyapunov method and initialization technique. Numerical and experiment examples are performed to illustrate our proposed control scheme with satisfactory results. Copyright © 2013 John Wiley & Sons, Ltd.