Weighted regularized extreme learning machine to model the discharge coefficient of side slots

In the current research, a modern learning machine algorithm named “Weighted Regularized Extreme Learning Machine (WRELM)" is implemented for the first time for the simulation of the coefficient of discharge of side slots. For this purpose, an effective variable on the coefficient of discharge of side slots is firstly introduced, then five distinctive WRELM models are produced by it for the estimation of the coefficient. In the next stage, a database is created for verification of WRELM results. it should be mentioned that 70% of the data are utilized for training the WRELM models, while the rest (i.e. 30%) for testing them. After that, the optimal number of hidden layer neurons as well as the best activation function of the WRELM algorithm are chosen. In addition, the best regularization parameter and also the weight function of the WRELM are achieved. By conducting a sensitivity analysis, the most effective variable for the simulation of the coefficient of discharge along with the WRELM superior model is introduced. The WRELM superior model estimates values of the coefficient of discharge with the maximum exactness and the highest correlation. For instance, the estimations of the correlation coefficient and scatter index for this model are computed to be 0.930 and 0.051, respectively. The sensitivity analysis shows that the ratio of the side slot crest height to its length and the Froude number should be considered as the most important input variables. A comparison between the WRELM with the ELM displays that the former works much better. Furthermore, an uncertainty analysis is executed for both models. Eventually, an equation is suggested for the estimation of the coefficient of discharge and a partial derivative sensitivity analysis is performed on it.     

A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

甘肃省陇东地区极端降水的时空特征

为阐明甘肃省陇东地区极端降水的变化规律,利用该地区13个气象台站1961~2015年的逐日降水资料,应用超门限峰值法、反距离加权法、线性倾向估计法、滑动平均法、Mann-Kendall突变分析法、复值Morlet小波分析法研究极端降水的时空变化特征。结果表明,陇东地区各站第95百分位极端降水阈值在27.8mm附近变化,即可以大雨事件作为极端降水事件进行监测;极端降水指数主要表现为从南向北递减的趋势,极端降水事件对环县和崆峒的影响较小;极端降水事件虽然在总量、强度上表现为减小趋势,但其发生频次及对总降水的贡献率逐渐增强;极端降水总量和极端降水强度周期变化均在21年左右能量最强,而极端降水频次和极端降水贡献率周期变化分别在28、5年左右能量最强。     

能源土边界面模型的应力更新算法及算例分析

水合物的存在会显著影响能源土的刚度、峰值强度与剪胀性。针对已有能源土模型的不足，结合边界面模型的建模思想，构建一个新的能源土边界面模型，模型参数较少，能够恰当反映能源土的应力-应变关系。计算能源土变形问题的核心在于正确积分塑性本构方程，应用完全隐式回退Euler算法，建立模型应力及塑性内变量的更新公式，并给出显式的一致性切线模量表达式。基于ABAQUS软件提供的二次开发接口，编写模型的用户材料子程序，应用已有试验数据验证程序正确性。最后应用开发的子程序对能源土的平面应变试验进行模拟，分析水合物饱和度对剪切带倾角与孔隙比的影响。     

含煤盆地深层“超饱和”煤层气形成条件

中国深层煤层气资源丰富，但总体勘探和认识程度较低，尚未形成较为系统的深层煤层气地质理论。通过解剖分析准噶尔盆地白家海凸起和鄂尔多斯盆地临兴区块深层"超饱和"煤层气井的试气/生产动态，估算原地游离气的含气量，分析了深层"超饱和"煤层气的形成条件。研究表明：①深层"超饱和"煤层气储层中除吸附气外，还含有原地游离气，用常规试气方法可直接获得气流，煤层气的产出不明显依赖于排水降压；②埋藏超过一定深度，在煤阶和温度的综合作用下，煤的吸附能力将随埋深的继续增加而降低，煤层中吸附气的饱和度有增加的趋势，在达到吸附饱和后，出现原地游离气并形成"超饱和"煤层气，盆地深层具有"超饱和"煤层气形成的优势条件；③由于地温梯度和压力梯度的不同，不同盆地"超饱和"煤层气出现的临界深度不同，异常高压和异常高热流可以降低深层"超饱和"煤层气形成的临界深度；④深层"超饱和"煤层气开发具有大大缩短见气时间、充分利用地层能量和累积产水量低等优势，有望成为未来煤层气勘探开发的一个重要领域。     

Ground robotics in tunnels: Keys and lessons learned after 10 years of research and experiments

The work reported in this article describes the research advances and the lessons learned by the Robotics, Perception and Real‐Time group over a decade of research in the field of ground robotics in confined environments. This study has primarily focused on localization, navigation, and communications in tunnel‐like environments. As will be discussed, this type of environment presents several special characteristics that often make well‐established techniques fail. The aim is to share, in an open way, the experience, errors, and successes of this group with the robotics community so that those that work in such environments can avoid (some of) the errors made. At the very least, these findings can be readily taken into account when designing a solution, without needing to sift through the technical details found in the papers cited within this text.     

不同层面倾角下锦屏一级水电站左岸板岩坡体破坏模式及能量特征

为了合理分析锦屏一级水电站左岸坡体的变形,选取坡体板岩进行巴西劈裂试验,分别研究了不同层面倾角下不同饱水率板岩的力学特性及能量特征。结果表明,板岩的抗拉强度随层面倾角的不断增加先减小后增加,其最大降幅达82%;同一层面倾角下,随着饱水程度的增加,板岩抗拉强度逐渐降低,在层面倾角为45°时,抗拉强度从1.64MPa降至0.52MPa,降幅达68%;试样层面倾角0°~90°的破坏受饱水率的影响较小,主要由层面倾角控制,破坏特征分为岩石拉伸型破坏、层面剪切破坏、基质-层面互剪型破坏、层面张拉破坏四种模式;试样破坏的累积能量随饱水程度的增加而不断减小,在相同饱水程度下,累积能量随层面倾角的增大而逐渐减小,累积能量的增长速率与荷载比成非线性关系,在轴向荷载达40%~80%时增长最快。     

Extended-state-observer-based dynamic surface control of flexible-joint robot systems with input saturation

This article presents an extended-state-observer-based dynamic surface control approach for flexible-joint robot systems with asymmetric input saturation and large unknown dynamic knowledge. Traditional controllers for flexible-joint robot systems usually use approximation technology to deal with unknown dynamics knowledge. Unlike the traditional control algorithm, this article utilizes an extended state observer to estimate the unknown dynamics. For the closed-loop system, the delay strategy handles the time-scale separation issue, the filtering system overcomes the “explosion of differentiation” caused by the repeated differentiation of auxiliary control signals, and the mean-value-theorem solves the input saturation problem of the actuator. The stability analysis implies that estimation errors of extended state observers (ESOs) and other state variables are semiglobally uniformly ultimately bounded. Compared with fuzzy control algorithms, the novel ESO-based dynamic surface control approach not only omits online learning time but also uses only a few control parameters to obtain satisfactory tracking performance. Finally, a comparison simulation experiment is provided to illustrate the effectiveness of the gained conclusions.