Bioinspired Mechanically Robust Metal‐Based Water Repellent Surface Enabled by Scalable Construction of a Flexible Coral‐Reef‐Like Architecture

Mechanical robustness is a central concern for moving artificial superhydrophobic surfaces to application practices. It is believed that bulk hydrophilic materials cannot be use to construct micro/nanoarchitectures for superhydrophobicity since abrasion‐induced exposure of hydrophilic surfaces leads to remarkable degradation of water repellency. To address this challenge, the robust mechanical durability of a superhydrophobic surface with metal (hydrophilic) textures, through scalable construction of a flexible coral‐reef‐like hierarchical architecture on various substrates including metals, glasses, and ceramics, is demonstrated. Discontinuous coral‐reef‐like Cu architecture is built by solid‐state spraying commercial electrolytic Cu particles (15–65 µm) at supersonic particle velocities. Subsequent flame oxidation is applied to introduce a porous hard surface oxide layer. Owing to the unique combination of the flexible coral‐reef‐like architecture and self‐similar manner of the fluorinated hard oxide surface layer, the coating surface retains its water repellency with an extremely low roll‐off angle (<2°) after cyclic sand‐paper abrasion, mechanical bending, sand‐grit erosion, knife‐scratching, and heavy loading of simulated acid rain droplets. Strong adhesion to glass, ceramics, and metals up to 34 MPa can be achieved without using adhesive. The results show that the present superhydrophobic coating can have wide outdoor applications for self‐cleaning and corrosion protection of metal parts.     

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method. In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.      

Novel model reference adaptive control architecture using semi‐initial excitation‐based switched parameter estimator

This paper is a generalization of the recently developed techniques of initial excitation (IE)–based adaptive control with an introduction to the definition of semi‐initial excitation (semi‐IE), a still more relaxed notion than IE. Classical adaptive controllers typically ensure Lyapunov stability of the extended error dynamics (tracking error + parameter estimation error) and asymptotic tracking, while requiring a stringent condition of persistence of excitation (PE) for parameter convergence. Of late, the authors have proposed a new adaptive control architecture, which guarantees parameter convergence under the online‐verifiable IE condition leading to exponential stability of the extended error dynamics. In earlier works, it has been established that the IE condition is significantly milder than the classical PE condition. The current work further slackens the excitation condition by proposing the concept of semi‐IE. The proposed adaptive controller is proved to ensure convergence of the parameter estimation error to a lower‐dimensional manifold under the weaker semi‐IE condition, while the stronger condition of IE guarantees convergence of the parameter estimation error to zero. The designed algorithm is shown to improve transient response of tracking error sufficiently in contrast to conventional adaptive controllers.     

APP软件性能效率研究

性能效率是APP软件的重要质量属性，但目前缺乏APP软件性能效率的通用模型。分析了APP软件的性能特征，基于ISO/IEC 25010标准提出了APP软件的性能效率模型，定义了APP软件性能效率的子特性和度量指标。基于提出的APP软件性能效率模型，通过实验对APP软件的性能效率进行了度量及相关分析。     

结合深度学习与相关反馈的遥感图像检索

目的 针对基于内容的图像检索存在低层视觉特征与用户对图像理解的高层语义不一致、图像检索的精度较低以及传统的分类方法准确度低等问题，提出一种基于卷积神经网络和相关反馈支持向量机的遥感图像检索方法。方法 通过对比度受限直方图均衡化算法对遥感图像进行预处理，限制遥感图像噪声的放大，采用自学习能力良好的卷积神经网络对遥感图像进行多层神经网络的监督学习提取丰富的图像特征，并将支持向量机作为基分类器，根据测试样本数据到分类超平面的距离进行排序得到检索结果，最后采用相关反馈策略对检索结果进行重新调整。结果 在UC Merced Land-Use遥感图像数据集上进行图像检索实验，在mAP（mean average precision）精度指标上，当检索返回图像数为100时，本文方法比LSH（locality sensitive Hashing）方法提高了29.4%，比DSH（density sensitive Hashing）方法提高了37.2%，比EMR（efficient manifold ranking）方法提高了68.8%，比未添加反馈和训练集筛选的SVM（support vector machine）方法提高了3.5%，对于平均检索速度，本文方法比对比方法中mAP精度最高的方法提高了4倍，针对复杂的遥感图像数据，本文方法的检索效果较其他方法表现出色。结论 本文提出了一种以距离评价标准为核心的反馈策略，以提高检索精度，并采用多距离结合的Top-k排序方法合理筛选训练集，以提高检索速度，本文方法可以广泛应用于人脸识别和目标跟踪等领域，对提升检索性能具有重要意义。     

Intelligent Power Compensation System Based on Adaptive Sliding Mode Control Using Soft Computing and Automation

The approach power compensator system (APCS) plays a role in the automatic carrier landing system (ACLS), and the performance of the APCS is affected by the carrier air-wake in the final-approach . In this paper, the importance of the APCS is verified through the analysis of the signal flow chart of the ACLS. Hence, it is necessary to suppress the carrier air-wake in order to improve the anti-interference ability. The adaptive sliding mode control (ASMC) not only has better dynamic tracking performance compared to the nonlinear mode, but also can efficiently resist the disturbance caused by the carrier air-wake. The design of the longitudinal control law of the ACLS is based on the carrier-based aircraft nonlinear model and the carrier air-wake model. It comprises the longitudinal guidance rate, autopilot (CAS) and the APCS. The ASMC is used to design the APCS to suppress the carrier air-wake. A comparison of the simulation results indicates that the design based on the ASMC has better anti-interference ability and can keep the velocity constant on the timely.     

基于最小方差的声线跟踪自适应分层算法

针对高精度水声定位系统中定位精度与计算量相互矛盾的问题,提出了基于最小方差的声线跟踪自适应分层算法。该算法根据声速在有限范围内规律变化的特点,对声速剖面全局搜索,通过各段声速散点到其拟合直线的总方差表示拟切分段与原始声速剖面的差别,利用最大差别找出最佳切分点,保留原始声速剖面特征,实现对声速剖面的简化。实验结果表明,该算法在保证定位精度的同时能够提高计算效率,具有良好的工程应用价值。     

某铅锌矿的三维地质模型及储量估算

针对矿山现有的地质信息数据等，建立了以利用Surpac软件的三维地表模型、矿体模型及地质数据库，对矿山资源储量进行计算。基于地质统计学的理论，建立某铅锌矿地表模型、钻孔数据库、矿体模型、块体模型，对矿体内样品进行组合分析统计，采用幂次距离反比法对块体品位进行估值，最后根据国内对地质矿产资源的分类方法，按照不同边界品位、工业品位等分类依据，得出资源储量核实报告，为铅锌矿的后续生产，提供了可靠保证。结果表明：通过构建该矿地质数据库，建立的三维模型，可对地质工程、采矿工程、储量估算、矿石品位动态管理等提供技术支持。     

Stabilisation of stochastic differential equations driven by G-Brownian motion via aperiodically intermittent control

ABSTRACT

As an emerging field, the G-Itô stochastic calculus plays an important role in describing the model uncertainty. Many interesting works have been done on stochastic differential equations driven by G-Brownian motion (G-SDEs). Among the theories and applications of G-SDEs, the stability is the vital important one. In this paper, we investigate the stabilisation for G-SDEs based on G-Lyapunov function and aperiodically adaptive intermittent controller. As an application, the sufficient conditions are established for the stabilisation of stochastic Cohen–Grossberg neural networks driven by G-Brownian motion (G-SCGNNs). Finally, an example is provided to illustrate the obtained results.     

宽带数字接收机IQ不平衡估计与自适应补偿算法

针对宽带调制解调技术中广泛存在的IQ不平衡问题,在IQ不平衡模型及补偿原理的分析基础上提出了一种宽带数字接收机IQ不平衡估计与自适应补偿算法。首先利用解调数据对IQ不平衡参数进行实时估计,然后利用估计参数对接收信号进行自适应补偿。实验结果表明,所提算法可以有效解决宽带调制解调系统中普遍存在的IQ不平衡问题,提升系统误码性能。