Configuration Synthesis and Grasping Performance Analysis of Multi-Loop Coupling Capture Mechanism for Launch and Recovery of Torpedo-Shaped Autonomous Underwater Vehicle

Research of capture mechanisms with strong capture adaptability and stable grasp is important to solve the problem of launch and recovery of torpedo-shaped autonomous underwater vehicles(AUVs).A multi-loop coupling capture mechanism with strong adaptability and high retraction rate has been proposed for the launch and recovery of torpedo-shaped AUVs with different morphological features.Firstly,the principle of capturing motion retraction is described based on the appearance characteristics of torpedo-shaped AUVs,and the configuration synthesis of the capture mechanism is carried out using the method of constrained chain synthesis.Secondly,the screw theory is employed to analyze the degree of freedom(DoF)of the capture mechanism.Then,the 3D model of the capture mechanism is established,and the kinematics and dynamics simulations are carried out.Combined with the capture orientation requirements of the capture mechanism,the statics and vibration characteristics analyses are carried out.Furthermore,considering the capture process and the underwater working environment,the motion characteristics and hydraulics characteristics of the capture mechanism are analyzed.Finally,a principle prototype is developed and the torpedo-shaped AUVs capture experiment is completed.The work provides technical reserves for the research and development of AUV capture special equipment.

Bidirectional rotating direct-current triboelectric nanogenerator with self-adaptive mechanical switching for harvesting reciprocating motion

Amid the growing interest in triboelectric nanogenerators(TENGs)as novel energy-harvesting devices,several studies have focused on direct current(DC)TENGs to generate a stable DC output for operating electronic devices.However,owing to the working mechanisms of conventional DC TENGs,generating a stable DC output from reciprocating motion remains a challenge.Accordingly,we propose a bidirectional rotating DC TENG(BiR-TENG),which can generate DC outputs,regardless of the direction of rotation,from reciprocating motions.The distinct design of the BiR-TENG enables the mechanical rectification of the alternating current output into a rotational-direction-dependent DC output.Furthermore,it allows the conversion of the rotational-direction-dependent DC output into a unidirectional DC output by adapting the configurations depending on the rotational direction.Owing to these tailored design strategies and subsequent optimizations,the BiR-TENG could generate an effective unidirectional DC output.Applications of the BiR-TENG for the reciprocating motions of swinging doors and waves were demonstrated by harnessing this output.This study demonstrates the potential of the BiR-TENG design strategy as an effective and versatile solution for energy harvesting from reciprocating motions,highlighting the suitability of DC outputs as an energy source for electronic devices.

Dynamic Economic Scheduling with Self-Adaptive Uncertainty in Distribution Network Based on Deep Reinforcement Learning

Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamicdecisions continuously. This paper proposed a dynamic economic scheduling method for distribution networksbased on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distributionnetwork is established considering the action characteristics of micro-gas turbines, and the dynamic schedulingmodel based on deep reinforcement learning is constructed for the new energy distribution network system with ahigh proportion of new energy, and the Markov decision process of the model is defined. Secondly, Second, for thechanging characteristics of source-load uncertainty, agents are trained interactively with the distributed networkin a data-driven manner. Then, through the proximal policy optimization algorithm, agents adaptively learn thescheduling strategy and realize the dynamic scheduling decision of the new energy distribution network system.Finally, the feasibility and superiority of the proposed method are verified by an improved IEEE 33-node simulationsystem.

Formal Modeling of Self-Adaptive Resource Scheduling in Cloud

A self-adaptive resource provisioning on demand is a critical factor in cloud computing.The selection of accurate amount of resources at run time is not easy due to dynamic nature of requests.Therefore,a self-adaptive strategy of resources is required to deal with dynamic nature of requests based on run time change in workload.In this paper we proposed a Cloud-based Adaptive Resource Scheduling Strategy(CARSS)Framework that formally addresses these issues and is more expressive than traditional approaches.The decision making in CARSS is based on more than one factors.TheMAPE-K based framework determines the state of the resources based on their current utilization.Timed-Arc Petri Net(TAPN)is used to model system formally and behaviour is expressed in TCTL,while TAPAAL model checker verifies the underline properties of the system.

In-situ interfacial passivation and self-adaptability synergistically stabilizing all-solid-state lithium metal batteries

The function of solid electrolytes and the composition of solid electrolyte interphase(SEI)are highly significant for inhibiting the growth of Li dendrites.Herein,we report an in-situ interfacial passivation combined with self-adaptability strategy to reinforce Li_(0.33)La_(0.557)TiO_(3)(LLTO)-based solid-state batteries.Specifically,a functional SEI enriched with LiF/Li_(3)PO_(4) is formed by in-situ electrochemical conversion,which is greatly beneficial to improving interface compatibility and enhancing ion transport.While the polarized dielectric BaTiO_(3)-polyamic acid(BTO-PAA,BP)film greatly improves the Li-ion transport kinetics and homogenizes the Li deposition.As expected,the resulting electrolyte offers considerable ionic conductivity at room temperature(4.3 x 10~(-4)S cm^(-1))and appreciable electrochemical decomposition voltage(5.23 V)after electrochemical passivation.For Li-LiFePO_(4) batteries,it shows a high specific capacity of 153 mA h g^(-1)at 0.2C after 100 cycles and a long-term durability of 115 mA h g^(-1)at 1.0 C after 800 cycles.Additionally,a stable Li plating/stripping can be achieved for more than 900 h at 0.5 mA cm^(-2).The stabilization mechanisms are elucidated by ex-situ XRD,ex-situ XPS,and ex-situ FTIR techniques,and the corresponding results reveal that the interfacial passivation combined with polarization effect is an effective strategy for improving the electrochemical performance.The present study provides a deeper insight into the dynamic adjustment of electrode-electrolyte interfacial for solid-state lithium batteries.

Self-adaptive bulk/surface engineering of Bi_(x)O_(y)Br_(z) towards enhanced photocatalysis:Current status and future challenges

The bulk/surface states of semiconductor photocatalysts are imperative parameters to maneuver their performance by significantly affecting the key processes of photocatalysis including light absorption,separation of charge carrier,and surface site reaction.Recent years have witnessed the encouraging progress of self-adaptive bulk/surface engineered Bi_(x)O_(y)Br_(z) for photocatalytic applications spanning various fields.However,despite the maturity of current research,the interaction between the bulk/surface state and the performance of Bi_(x)O_(y)Br_(z) has not yet been fully understood and highlighted.In this regard,a timely tutorial overview is quite urgent to summarize the most recent key progress and outline developing obstacles in this exciting area.Herein,the structural characteristics and fundamental principles of Bi_(x)O_(y)Br_(z)for driving photocatalytic reaction as well as related key issues are firstly reviewed.Then,we for the first time summarized different self-adaptive engineering processes over Bi_(x)O_(y)Br_(z)followed by a classification of the generation approaches towards diverse Bi_(x)O_(y)Br_(z)materials.The features of different strategies,the up-to-date characterization techniques to detect bulk/surface states,and the effect of bulk/surface states on improving the photoactivity of Bi_(x)O_(y)Br_(z)in expanded applications are further discussed.Finally,the present research status,challenges,and future research opportunities of self-adaptive bulk/surface engineered Bi_(x)O_(y)Br_(z)are prospected.It is anticipated that this critical review can trigger deeper investigations and attract upcoming innovative ideas on the rational design of Bi_(x)O_(y)Br_(z)-based photocatalysts.

A WSN Node Fault Diagnosis Model Based on BRB with Self-Adaptive Quality Factor

Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and wireless data transmission, the data collected by WSNs containnoisy data, leading to unreliable data among the data features extracted duringfault diagnosis. To reduce the influence of unreliable data features on faultdiagnosis accuracy, this paper proposes a belief rule base (BRB) with a selfadaptivequality factor (BRB-SAQF) fault diagnosis model. First, the datafeatures required for WSN node fault diagnosis are extracted. Second, thequality factors of input attributes are introduced and calculated. Third, themodel inference process with an attribute quality factor is designed. Fourth,the projection covariance matrix adaptation evolution strategy (P-CMA-ES)algorithm is used to optimize the model’s initial parameters. Finally, the effectivenessof the proposed model is verified by comparing the commonly usedfault diagnosis methods for WSN nodes with the BRB method consideringstatic attribute reliability (BRB-Sr). The experimental results show that BRBSAQFcan reduce the influence of unreliable data features. The self-adaptivequality factor calculation method is more reasonable and accurate than thestatic attribute reliability method.

Global and International Security Under Spatial Grasp Paradigm

Global and international security cannot be provided from a single point or a set of separate points whatever powerful these might be(even with quantum supercomputers!).It should rather be deeply embedded and integrated with bodies of real systems wherever in physical,virtual,or combined spaces they may exist.So global security capabilities should not only be distributed,but rather be really spatial,self-organized,and dynamic,also exhibiting overall integrity,awareness,and consciousness features.The paper describes applicability of the patented and revealed in 10 books Spatial Grasp Model and Technology(SGT)and its basic Spatial Grasp Language(SGL)which conceptually and functionally match security problems of large distributed and heterogeneous systems.It investigates very practical security solutions for finding and tracing distribution of forbidden items,world roaming criminals,recovery from natural and human-made disasters,tracing and elimination of moving dangerous objects in terrestrial and celestial spaces,as well as analysis and restoration of damaged transport networks.It advises how different security infrastructures can be organized and managed,and how to cooperate and integrate within global security systems with higher awareness and consciousness levels over them.The provided security-oriented version of SGL can be quickly implemented and integrated with existing distributed management and security systems.

基于GRASPS设计工具的八年级英语项目化教学实践研究——以“情景剧表演”为例

《英语课程标准》的基本原则中提到:要加强课程综合,注重关联,突出实践。然而传统的英语课堂只重视学生对英语知识的机械输入和积累,忽视学生英语学习过程的启发,特别是英语语言的实践活动,导致学生被动学习,课堂教学低效。笔者基于八年级学生的认知特点,以生活化的情景剧为表现形式,依托GRASPS设计工具和项目化学习进行教学改革,创设真实情境、突出学生主体、建立有效评价,给学生主动参与、体验、实践的机会,提升学生运用所学语言和跨学科知识创造性解决问题的能力。

基于GRASP-PR混合算法的多目标EV充电任务序列优化模型

提出基于GRASP-PR混合算法的多目标EV充电任务序列优化模型,以提高配电网的平峰填谷能力,确保其稳定运行。根据EV出行特点,在分析无序充电模式对配电网负荷峰谷差影响的基础上,构建EV充电任务序列优化模型,采用引入路径重连策略的贪心随机自适应搜索算法对优化模型求解,确定最优EV充电任务序列调度方案。实验结果表明:在无序充电模式下,并网充电EV数量越多,配电网负荷峰谷差越大;该优化模型可实现EV充电任务序列的优化控制,达到平峰填谷效果,降低配电网运行成本、EV充电成本。

Numerical simulation of LWD resistivity response of carbonate formation using self-adaptive hp-FEM

Most of the carbonate formation are highly heterogeneous with cavities of different sizes, which makes the prediction of cavity-filled reservoir in carbonate rocks difficult. Large cavities in carbonate formations pose serious threat to drilling operations. Logging-whiledrilling （LWD） is currently used to accurately identify and evaluate cavities in reservoirs during drilling. In this study, we use the self-adaptive hp-FEM algorithm simulate and calculate the LWD resistivity responses of fracture-cavity reservoir cavities. Compared with the traditional h-FEM method, the self-adaptive hp-FEM algorithm has the characteristics of the self-adaptive mesh refinement and the calculations exponentially converge to highly accurate solutions. Using numerical simulations, we investigated the effect of the cavity size, distance between cavity and borehole, and transmitted frequency on the LWD resistivity response. Based on the results, a method for recognizing cavities is proposed. This research can provide the theoretical basis for the accurate identification and quantitative evaluation of various carbonate reservoirs with cavities encountered in practice.

EVOLUTIONARY FUZZY GUIDANCE LAW WITH SELF-ADAPTIVE REGION

Effective guidance is one of the most important tasks to the performance of air-to-air missile. The fuzzy logic controller is able to perform effectively even in situations where the information about the plant is inaccurate and the operating conditions are uncertain. Based on the proportional navigation, the fuzzy logic and the genetic algorithm are combined to develop an evolutionary fuzzy navigation law with self-adapt region for the air-to-air missile guidance. The line of sight (LOS) rate and the closing speed between the missile and the target are inputs of the fuzzy controller. The output of the fuzzy controller is the commanded acceleration. Then a nonlinear function based on the conventional fuzzy logic control is imported to change the region. This nonlinear function can be changed with the input variables. So the dynamic change of the fuzzy variable region is achieved. The guidance law is optimized by the genetic algorithm. Simulation results of air-to-air missile attack using MATLAB show that the method needs less acceleration and shorter flying time, and its realization is simple.[KH*3/4D]

BIO-INSPIRED SELF-ADAPTIVE MANUFACTURING SYSTEM CONTROL ARCHITECTURE

Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.

A new breakthrough:ESD using a newly developed grasping type scissor forceps for early gastrointestinal tract neoplasms

Endoscopic submucosal dissection(ESD) has allowed the achievement of histologically curative en bloc resection of gastrointestinal neoplasms regardless of size,permitting the resection of previously non-resectable tumors.The ESD technique for treatment of early gastric cancer has spread rapidly in Japan and a few other Asian countries due to its excellent eradication rate compared to endoscopic mucosal resection.Although numerous electrosurgical knives have been developed for ESD,technical difficulties and high complication rates(bleeding and perforation) have limited their use worldwide.We developed the grasping type scissor forceps(GSF) to resolve such ESD-related problems.Our animal and preliminary clinical studies showed that ESD using GSF is a safe(no intraoperative complication) and technically efficient(curative en bloc resection rate 92%) method for dissection of early gastrointestinal tumors.The use of GSF is a promising option for performing ESD on early stage GI tract tumors both safely and effectively.

FORCE OPTIMIZATION OF GRASPING BY ROBOTIC HANDS

It is important for robotic hands to obtain optimal grasping performance inthe meanwhile balancing external forces and maintaining grasp stability. The problem of forceoptimization of grasping is solved in the space of joint torques. A measure of grasping performanceis presented to protect joint actuators from working in heavy payloads. The joint torques arecalculated for the optimal performance under the frictional constraints and the physical limits ofmotor outputs. By formulating the grasping forces into the explicit function of joint torques, thefrictional constraints imposed on the grasping forces are transformed into the constraints on jointtorques. Without further simplification, the nonlinear frictional constraints can be simply handledin the process of optimization. Two numerical examples demonstrate the simplicity and effectivenessof the approach.

Stable grasping gesture analysis of a cable-driven underactuated robotic hand

The stable grasping gesture of a novel cable-driven robotic hand is analyzed. The robotic hand is underactuated, using tendon-pulley transmission and a parallel four-linkage mechanism to realize grasp. The structure design and a basic grasping strategy of one finger was introduced. According to the established round object enveloping grasp model, the relationship between the contacting and driving forces in a finger and stable grasping conditions were expounded. A method of interpolation and iteration was proposed to obtain the stable grasping gesture of the cable-driven hand grasping a round target. Quasi-statics analysis in ADAMS validated the variation of grasping forces, which illustrated the feasibility and validity of the proposed analytical method. Three basic types of grasping gestures of the underactuated hand were obtained on the basis of the relationship between the contact forces and position of a grasped object.

A New Grasping Mode Based on a Sucked-type Underactuated Hand

Robot hands have been developing during the last few decades. There are many mechanical structures and analyti?cal methods for di erent hands. But many tough problems still limit robot hands to apply in homelike environment. The ability of grasping objects covering a large range of sizes and various shapes is fundamental for a home service robot to serve people better. In this paper, a new grasping mode based on a novel sucked?type underactuated(STU) hand is proposed. By combining the flexibility of soft material and the e ect of suction cups, the STU hand can grasp objects with a wide range of sizes, shapes and materials. Moreover, the new grasping mode is suitable for some situations where the force closure is failure. In this paper, we deduce the e ective range of sizes of objects which our hand using the new grasping mode can grasp. Thanks to the new grasping mode, the ratio of grasping size between the biggest object and the smallest is beyond 40, which makes it possible for our robot hand to grasp diverse objects in our daily life. For example, the STU hand can grasp a soccer(220 mm diameter, 420 g) and a fountain pen(9 mm diameter, 9 g). What’s more, we use the rigid body equilibrium conditions to analysis the force condition. Experiment evaluates the high load capacity, stability of the new grasping mode and displays the versatility of the STU hand. The STU hand has a wide range of applications especially in unstructured environment.

Dynamics and Stability of Blind Grasping of a 3-Dimensional Object under Non-holonomic Constraints

A mathematical model expressing the motion of a pair of multi-DOF robot fingers with hemi-spherical ends, grasping a 3-D rigid object with parallel fiat surfaces, is derived, together with non-holonomic constraints. By referring to the fact that humans grasp an object in the form of precision prehension, dynamically and stably by opposable forces, between the thumb and another finger （index or middle finger）, a simple control signal constructed from finger-thumb opposition is proposed, and shown to realize stable grasping in a dynamic sense without using object information or external sensing （this is called ＂blind grasp＂ in this paper）. The stability of grasping with force/torque balance under non-holonomic constraints is analyzed on the basis of a new concept named ＂stability on a manifold＂. Preliminary simulation results are shown to verify the validity of the theoretical results.

Hand-eye-vision based control for an inspection robot's autonomous line grasping

In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.

Self-adaptive learning based discrete differential evolution algorithm for solving CJWTA problem

Cooperative jamming weapon-target assignment （CJWTA） problem is a key issue in electronic countermeasures （ECM）. Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness is presented. Final y, a model of the CJWTA problem is constructed. In order to solve the CJWTA problem efficiently, a self-adaptive learning based discrete differential evolution （SLDDE） algorithm is proposed by introduc-ing a self-adaptive learning mechanism into the traditional discrete differential evolution algorithm. The SLDDE algorithm steers four candidate solution generation strategies simultaneously in the framework of the self-adaptive learning mechanism. Computa-tional simulations are conducted on ten test instances of CJWTA problem. The experimental results demonstrate that the proposed SLDDE algorithm not only can generate better results than only one strategy based discrete differential algorithms, but also outper-forms two algorithms which are proposed recently for the weapon-target assignment problems.