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A novel industrial AGV control strategy based on dual-wheel chassis model 一种基于双轮底盘模型的新型工业AGV控制策略
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-04-07 DOI: 10.1108/aa-09-2021-0122
Hua Ding, Yanhong Huang, Jianqi Shi, Qi Shi, Yang Yang
PurposeAutomatic guided vehicles (AGVs) are widely used in industrial fields. But most control strategies merely take the lateral force into consideration. This will reduce the accuracy, stability and robustness and will pay additional costs. Therefore, this paper aims to design a control strategy that initially considers lateral force. Thereby, it will improve the accuracy, stability and robustness and reduce the overall cost of AGV.Design/methodology/approachTo achieve the goal of comprehensively improving AGV operating performance, this paper presents a new scheme, combining the dual-wheeled chassis model (DCM) using proportional–integral–differential (PID) control and a supporting quick response (QR) code navigation technology. DCM is the core, which analyzes the deviation caused by lateral force. Then, DCM with PID control by the control law is combined to suppress the errors. Meanwhile, QR code navigation technology provides effective data support for the control strategy.FindingsMost AGV experiments are carried out in a standard environment. However, this study prepares unfavorable scenarios and operating conditions for the experiments that generate detailed data to demonstrate this study’s strategy, which can make an accurate, stable and robust operation process of AGV under various adverse environmental and mechanical factors.Originality/valueThis study proposed DCM, fully considering lateral force and converting the force into velocity. Subsequently, PID controls the speed of two wheels to reduce the error. QR code provides an efficient and low – cost way to obtain information. The three are cleverly combined as a novel industrial AGV control strategy, which can comprehensively improve the operating performance while reducing overall costs.
目的自动导引车(agv)在工业领域有着广泛的应用。但大多数控制策略只考虑侧向力。这将降低准确性、稳定性和鲁棒性,并将支付额外的成本。因此,本文旨在设计一种初步考虑侧向力的控制策略。从而提高AGV的精度、稳定性和鲁棒性,降低AGV的整体成本。为全面提高AGV的运行性能,本文提出了一种将采用比例-积分-微分(PID)控制的双轮底盘模型(DCM)与配套的快速响应(QR)码导航技术相结合的新方案。以DCM为核心,分析侧向力引起的偏差。然后,通过控制律将DCM与PID控制相结合来抑制误差。同时,二维码导航技术为控制策略提供了有效的数据支持。大多数AGV实验都是在标准环境中进行的。然而,本研究为实验准备了不利的场景和运行条件,产生了详细的数据来证明本研究的策略,可以使AGV在各种不利的环境和机械因素下准确、稳定和稳健的运行过程。独创性/价值本研究提出DCM,充分考虑侧向力,将力转化为速度。随后,PID控制两个车轮的速度,以减少误差。二维码提供了一种高效、低成本的获取信息的方式。三者巧妙结合,形成一种新型的工业AGV控制策略,在全面提高运行性能的同时降低整体成本。
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引用次数: 2
Industrial process data visualization based on a deep enhanced t-distributed stochastic neighbor embedding neural network 基于深度增强t分布随机邻居嵌入神经网络的工业过程数据可视化
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-03-18 DOI: 10.1108/aa-09-2021-0123
Weipeng Lu, Xue-feng Yan
PurposeThe purpose of this paper is to propose a approach for data visualization and industrial process monitoring.Design/methodology/approachA deep enhanced t-distributed stochastic neighbor embedding (DESNE) neural network is proposed for data visualization and process monitoring. The DESNE is composed of two deep neural networks: stacked variant auto-encoder (SVAE) and a deep label-guided t-stochastic neighbor embedding (DLSNE) neural network. In the DESNE network, SVAE extracts informative features of the raw data set, and then DLSNE projects the extracted features to a two dimensional graph.FindingsThe proposed DESNE is verified on the Tennessee Eastman process and a real data set of blade icing of wind turbines. The results indicate that DESNE outperforms some visualization methods in process monitoring.Originality/valueThis paper has significant originality. A stacked variant auto-encoder is proposed for feature extraction. The stacked variant auto-encoder can improve the separation among classes. A deep label-guided t-SNE is proposed for visualization. A novel visualization-based process monitoring method is proposed.
目的提出一种数据可视化和工业过程监控的方法。提出了一种深度增强t分布随机邻居嵌入(DESNE)神经网络,用于数据可视化和过程监控。DESNE由两个深度神经网络组成:堆叠变量自编码器(SVAE)和深度标签引导的t随机邻居嵌入(DLSNE)神经网络。在DESNE网络中,SVAE提取原始数据集的信息特征,然后DLSNE将提取的特征投影到二维图中。在田纳西伊士曼工艺和风力涡轮机叶片结冰的真实数据集上验证了所提出的DESNE。结果表明,DESNE在过程监控方面优于一些可视化方法。原创性/价值这篇论文有显著的原创性。提出了一种叠变自编码器用于特征提取。层叠式变量自编码器可以改善类间的分离。提出了一种深度标签引导的t-SNE可视化方法。提出了一种新的基于可视化的过程监控方法。
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引用次数: 5
Structure design and optimization of ground moving and pole climbing inspection robot 地移爬杆检测机器人结构设计与优化
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-03-10 DOI: 10.1108/aa-12-2021-0168
Changlong Ye, Yunfei Zang, Suyang Yu, Chun-ying Jiang
PurposeThe purpose of this paper is to demonstrate a multipurpose inspection robot that can both walk on the ground and climb on poles. The structure design, size optimization, kinematics analysis, experiment and arithmetic of the robot are discussed in the paper.Design/methodology/approachThe robot consists of three adjustable modules and a two-degree-of-freedom parallel mechanism in tandem, and the wheel-finger mechanism of each module can realize wheel-finger opening and closing for fast movement and obstacle crossing. This paper uses geometric analysis and simulation analysis to derive size optimization, and vector coordinate method to derive kinematics. Finally, the experiment is carried out by simulating the working environment of the robot.FindingsThe robot can realize ground walking and ground turning through the robot entity prototype experiment on the built working environment and efficiently realize 0°–90° pole climbing by the assemble design, optimization and machining. In addition, the robot can also smoothly complete the state transition process from 0° ground to 90° pole climbing. Furthermore, the robot shows good environmental self-adaptation and can complete daily inspection work.Originality/valueThe robot can pitch and yaw at a large angle and has six-legged characteristics. It is a multipurpose inspection robot that can walk on the ground and climb on poles. And through structure design, size optimization, kinematics analysis and simulation, the existing robots’ common shortcomings such as poor barrier-crossing ability and poor environmental adaptability are solved.
本文的目的是演示一种既能在地面行走又能在杆子上攀爬的多用途巡检机器人。本文讨论了机器人的结构设计、尺寸优化、运动学分析、实验和算法。该机器人由三个可调模块和一个两自由度并联机构串联组成,每个模块的轮指机构可实现轮指开合,实现快速移动和过障。本文采用几何分析和仿真分析方法进行尺寸优化推导,采用矢量坐标法进行运动学推导。最后,通过模拟机器人的工作环境进行实验。通过在搭建的工作环境下的机器人实体样机实验,该机器人可以实现地面行走和地面转弯,并通过装配设计、优化和加工,高效地实现0°-90°极点爬取。此外,机器人还能顺利完成从0°地面到90°爬极的状态转换过程。此外,该机器人具有良好的环境自适应能力,能够完成日常巡检工作。该机器人可以大角度俯仰和偏航,具有六条腿的特征。它是一种可以在地面行走和爬杆的多用途巡检机器人。并通过结构设计、尺寸优化、运动学分析与仿真,解决了现有机器人过障能力差、环境适应能力差等共性缺点。
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引用次数: 1
Intelligent assembly assistance for hull structure construction based on optical projection 基于光学投影的船体结构智能装配辅助
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-02-15 DOI: 10.1108/aa-05-2021-0061
Y. Zhu, Jun Yang, Hongwei Zhang, Wenmin Zhu, Jie Wang, Zelin Zhou
PurposeMarking and inspecting are key steps in hull structure construction. However, currently most marking and inspecting operations are still carried out manually, which leads to low assembly efficiency and quality. This paper aims to solve these problems through the application of digital technology: the optical projection and machine vision.Design/methodology/approachFirst, the assembly process model of hull construction is established in 3D design environment. Second, the process information is presented to workers in a virtual form through optical projector, which provides accurate guidance for the manual operation. On this basis, the workers can complete welding and assembly operations readily. Finally, the machine vision method is used to check the assembly results, which can decrease the subjective errors.FindingsA rapid and accurate assembly positioning for hull structure construction is realized based on optical projection, which can avoid the pollution caused by the marking machine and the error caused by human.Originality/valueThis paper combines the advantages of optical projection and machine vision to the field of shipbuilding. The shortcomings of the traditional marking and inspection methods is effectively solved, which may provide a new way for enhancing the assembly efficiency and quality.
目的标记和检验是船体结构施工的关键环节。然而,目前大多数标记和检测操作仍然是手工进行的,这导致装配效率和质量不高。本文旨在通过光学投影和机器视觉等数字技术的应用来解决这些问题。设计方法首先,在三维设计环境下建立船体结构装配过程模型。其次,通过光学投影仪将工艺信息以虚拟的形式呈现给工人,为手工操作提供准确的指导。在此基础上,工人可以轻松完成焊接和组装操作。最后,采用机器视觉方法对装配结果进行检验,减少了主观误差。基于光学投影实现了船体结构施工中快速准确的装配定位,避免了打标机造成的污染和人为造成的误差。本文将光学投影和机器视觉的优势结合到造船领域。有效地解决了传统标记和检测方法的不足,为提高装配效率和质量提供了一条新的途径。
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引用次数: 0
Vibration and position tracking control for a flexible Timoshenko robot arm with disturbance rejection mechanism 具有抗扰机构的柔性Timoshenko机械臂振动与位置跟踪控制
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-01-28 DOI: 10.1108/aa-11-2021-0154
Yan Yang, Jun Shi, Zhijie Liu, Shuangyin Liu
PurposeThis paper aims to study the boundary disturbance rejection control design for a flexible Timoshenko robot arm to diminish external disturbances and achieve desired angle tracking, with system vibration and elastic deformation considered.Design/methodology/approachThis study introduces disturbance observer and disturbance rejection mechanism into the boundary control design for flexible Timoshenko robot arm systems. The uniform bounded stability of controlled systems is proved via Lyapunov analysis without any simplification of the infinite-dimensional system dynamics.FindingsThe proposed boundary disturbance rejection control scheme can effectively suppress vibrations and shear deformations, achieve the required angular positioning and reject external disturbances. Numerical simulations developed by the finite difference method are adapted to demonstrate the validity of the designed controller.Originality/valueThe originality of this study is to design boundary disturbance rejection control to suppress vibrations and shear deformations for the flexible Timoshenko robot arm, thereby improving the performance and control accuracy of the system.
目的研究考虑系统振动和弹性变形的柔性Timoshenko机械臂的边界扰动抑制控制设计,以减少外部扰动并实现期望的角度跟踪。设计/方法/方法本研究将扰动观测器和扰动抑制机制引入柔性Timoshenko机械臂系统的边界控制设计中。在不简化无穷维系统动力学的情况下,通过李雅普诺夫分析证明了受控系统的一致有界稳定性。发现所提出的边界扰动抑制控制方案可以有效地抑制振动和剪切变形,实现所需的角度定位,并抑制外部扰动。采用有限差分法进行的数值模拟验证了所设计控制器的有效性。独创性/价值本研究的独创性是为柔性Timoshenko机械臂设计边界扰动抑制控制,以抑制振动和剪切变形,从而提高系统的性能和控制精度。
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引用次数: 4
Integrated fault detection for industrial process monitoring based on multi-dimensional Taylor network 基于多维Taylor网络的工业过程监控综合故障检测
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-01-27 DOI: 10.1108/aa-06-2021-0076
Chenlong Li, Changshun Yuan, Xiaoshu Ma, Wen-Liang Chen, Jun Wang
PurposeThis paper aims to provide a novel integrated fault detection method for industrial process monitoring.Design/methodology/approachA novel integrated fault detection method based on the combination of Mallat (MA) algorithm, weight-elimination (WE) algorithm, conjugate gradient (CG) algorithm and multi-dimensional Taylor network (MTN) dynamic model, namely, MA-WE-CG-MTN, is proposed in this paper. First, MA algorithm is taken as data pre-processing. Second, in virtue of approximation ability and low computation complexity owing to the simple structure of MTN, MTN dynamic models are constructed for each frequency band. Furthermore, the CG algorithm is used to discipline the model parameters and the outputs of MTN model of each frequency band are gained. Third, the authors introduce the WE algorithm to cut down the number of middle layer nodes of MTN, reducing the complexity of the network. Finally, the outputs of MTN model for each frequency band are superimposed to achieve outputs of MTN model, and fault detection is proceeded by the residual error generator based on the difference between the output of MTN model and the actual output.FindingsThe novel proposed method is used to perform fault detection for industrial process monitoring effectively, such as the Benchmark Simulation Model 1 wastewater treatment process.Originality/valueThe novel proposed method has generality and provides considerably improved performance and effectiveness, which is used to perform fault detection for industrial process monitoring. The proposed method has good robustness, low complexity and easy implementation.
目的为工业过程监控提供一种新的集成故障检测方法。本文提出了一种基于Mallat (MA)算法、加权消除(WE)算法、共轭梯度(CG)算法和多维泰勒网络(MTN)动态模型相结合的新型综合故障检测方法,即MA-WE-CG-MTN。首先,采用MA算法对数据进行预处理。其次,利用MTN结构简单,具有较强的逼近能力和较低的计算复杂度,对每个频段构建MTN动态模型。利用CG算法对模型参数进行约束,得到各频段MTN模型的输出。第三,引入WE算法,减少MTN中间层节点的数量,降低网络的复杂度。最后,将MTN模型各频段的输出叠加,得到MTN模型的输出,并根据MTN模型输出与实际输出的差值,由残差发生器进行故障检测。该方法可有效地用于工业过程监控的故障检测,例如基准模拟模型1废水处理过程。该方法具有通用性,并显著提高了性能和有效性,可用于工业过程监控的故障检测。该方法鲁棒性好,复杂度低,易于实现。
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引用次数: 2
An industrial intelligent grasping system based on convolutional neural network 基于卷积神经网络的工业智能抓取系统
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-01-13 DOI: 10.1108/aa-03-2021-0036
Jiang Daqi, Wang Hong, Zhou Bin, Wei Chunfeng
PurposeThis paper aims to save time spent on manufacturing the data set and make the intelligent grasping system easy to deploy into a practical industrial environment. Due to the accuracy and robustness of the convolutional neural network, the success rate of the gripping operation reached a high level.Design/Methodology/ApproachThe proposed system comprises two diverse kinds of convolutional neuron network (CNN) algorithms used in different stages and a binocular eye-in-hand system on the end effector, which detects the position and orientation of workpiece. Both algorithms are trained by the data sets containing images and annotations, which are generated automatically by the proposed method.FindingsThe approach can be successfully applied to standard position-controlled robots common in the industry. The algorithm performs excellently in terms of elapsed time. Procession of a 256 × 256 image spends less than 0.1 s without relying on high-performance GPUs. The approach is validated in a series of grasping experiments. This method frees workers from monotonous work and improves factory productivity.Originality/ValueThe authors propose a novel neural network whose performance is tested to be excellent. Moreover, experimental results demonstrate that the proposed second level is extraordinary robust subject to environmental variations. The data sets are generated automatically which saves time spent on manufacturing the data set and makes the intelligent grasping system easy to deploy into a practical industrial environment. Due to the accuracy and robustness of the convolutional neural network, the success rate of the gripping operation reached a high level.
本文旨在节省制造数据集的时间,并使智能抓取系统易于部署到实际工业环境中。由于卷积神经网络的准确性和鲁棒性,使得抓取操作的成功率达到了很高的水平。设计/方法/方法所提出的系统包括两种不同的卷积神经元网络(CNN)算法,用于不同的阶段,以及末端执行器上的双目眼手系统,用于检测工件的位置和方向。这两种算法都是通过包含图像和注释的数据集来训练的,这些数据集是由所提出的方法自动生成的。该方法可成功应用于工业中常见的标准位置控制机器人。该算法在运行时间方面表现出色。在不依赖高性能gpu的情况下,处理256 × 256图像的时间不到0.1 s。该方法在一系列抓取实验中得到了验证。这种方法使工人从单调的工作中解放出来,提高了工厂的生产率。原创性/价值作者提出了一种新的神经网络,其性能被证明是优秀的。此外,实验结果表明,所提出的第二层次对环境变化具有非凡的鲁棒性。自动生成数据集,节省了制造数据集的时间,使智能抓取系统易于部署到实际工业环境中。由于卷积神经网络的准确性和鲁棒性,使得抓取操作的成功率达到了很高的水平。
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引用次数: 1
Multi-sensor optimal deployment based efficient and synchronous data acquisition in large three-dimensional physical similarity simulation 基于多传感器优化部署的大型三维物理相似性仿真中高效同步数据采集
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-01-05 DOI: 10.1108/aa-06-2021-0074
Yuyu Hao, Shugang Li, Tian-cai Zhang
PurposeThis paper aims to propose a deployment optimization and efficient synchronous acquisition method for compressive stress sensors used by stress distribution law research based on the genetic algorithm and numerical simulations. The authors established a new method of collecting the mining compressive stress-strain distribution data to address the problem of the number of sensors and to optimize the sensor locations in physical similarity simulations to improve the efficiency and accuracy of data collection.Design/methodology/approachFirst, numerical simulations were used to obtain the compressive stress distribution curve under specific mining conditions. Second, by comparing the mean square error between a fitted curve and simulation data for different numbers of sensors, a genetic algorithm was used to optimize the three-dimensional (3D) spatial deployment of sensors. Third, the authors designed an efficient synchronous acquisition module to allow distributed sensors to achieve synchronous and efficient acquisition of hundreds of data points through a built-in on-board database and a synchronous sampling communication structure.FindingsThe sensor deployment scheme was established through the genetic algorithm, A synchronous and selective data acquisition method was established for reduced the amount of sensor data required under synchronous acquisition and improved the system acquisition efficiency. The authors obtained a 3D compressive stress distribution when the advancement was 200 m on a large-scale 3D physical similarity simulation platform.Originality/valueThe proposed method provides a new optimization method for sensor deployment in physical similarity simulations, which improves the efficiency and accuracy of system data acquisition, providing accurate acquisition data for experimental data analysis.
目的本文旨在基于遗传算法和数值模拟,提出一种用于应力分布规律研究的压应力传感器的部署优化和高效同步采集方法。作者建立了一种收集采矿压缩应力-应变分布数据的新方法,以解决传感器数量的问题,并在物理相似性模拟中优化传感器位置,从而提高数据收集的效率和准确性。设计/方法/方法首先,使用数值模拟获得特定开采条件下的压应力分布曲线。其次,通过比较不同数量传感器的拟合曲线和模拟数据之间的均方误差,使用遗传算法优化传感器的三维空间部署。第三,作者设计了一个高效的同步采集模块,通过内置的机载数据库和同步采样通信结构,使分布式传感器能够实现数百个数据点的同步高效采集。发现通过遗传算法建立了传感器部署方案,建立了一种同步选择性数据采集方法,减少了同步采集所需的传感器数据量,提高了系统采集效率。作者在大型三维物理相似性模拟平台上获得了推进200米时的三维压应力分布。独创性/价值该方法为物理相似性模拟中的传感器部署提供了一种新的优化方法,提高了系统数据采集的效率和准确性,为实验数据分析提供了准确的采集数据。
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引用次数: 0
A gas migration law study of a large-scale 3D physical similarity simulation with an adaptive Kalman filter algorithm 基于自适应卡尔曼滤波算法的大规模三维物理相似模拟气体运移规律研究
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-01-04 DOI: 10.1108/aa-06-2021-0084
Yuyu Hao, Shugang Li, Tian-cai Zhang
PurposeIn this study, a physical similarity simulation plays a significant role in the study of crack evolution and the gas migration mechanism. A sensor is deployed inside a comparable artificial rock formation to assure the accuracy of the experiment results. During the building of the simulated rock formation, a huge volume of acidic gas is released, causing numerous sensor measurement mistakes. Additionally, the gas concentration estimation approach is subject to uncertainty because of the complex rock formation environment. As a result, the purpose of this study is to introduce an adaptive Kalman filter approach to reduce observation noise, increase the accuracy of the gas concentration estimation model and, finally, determine the gas migration law.Design/methodology/approachFirst, based on the process of gas floatation-diffusion and seepage, the gas migration model is established according to Fick’s second law, and a simplified modeling method using diffusion flux instead of gas concentration is presented. Second, an adaptive Kalman filter algorithm is introduced to establish a gas concentration estimation model, taking into account the model uncertainty and the unknown measurement noise. Finally, according to a large-scale physical similarity simulation platform, a thorough experiment about gas migration is carried out to extract gas concentration variation data with certain ventilation techniques and to create a gas chart of the time-changing trend.FindingsThis approach is used to determine the changing process of gas distribution for a certain ventilation mode. The results match the rock fissure distribution condition derived from the microseismic monitoring data, proving the effectiveness of the approach.Originality/valueFor the first time in large-scale three-dimensional physical similarity simulations, the adaptive Kalman filter data processing method based on the inverse Wishart probability density function is used to solve the problem of an inaccurate process and measurement noise, laying the groundwork for studying the gas migration law and determining the gas migration mechanism.
目的在本研究中,物理相似模拟对裂缝演化和气体运移机理的研究具有重要意义。为了保证实验结果的准确性,将传感器部署在一个可比较的人工岩层中。在模拟岩层形成过程中,大量酸性气体被释放,导致传感器测量出现大量错误。此外,由于地层环境复杂,瓦斯浓度估算方法存在不确定性。因此,本研究的目的是引入一种自适应卡尔曼滤波方法来降低观测噪声,提高气体浓度估计模型的精度,最终确定气体运移规律。设计/方法/途径首先,基于气体的漂浮-扩散和渗流过程,根据菲克第二定律建立了气体运移模型,提出了一种以扩散通量代替气体浓度的简化建模方法。其次,引入自适应卡尔曼滤波算法,建立了考虑模型不确定性和未知测量噪声的气体浓度估计模型;最后,根据大型物理相似模拟平台,进行了深入的气体运移实验,提取了特定通风技术下的气体浓度变化数据,并绘制了随时间变化趋势的气体图。结果该方法用于确定某一通风方式下气体分布的变化过程。结果与微震监测资料得出的岩体裂隙分布条件吻合,证明了该方法的有效性。独创性/价值首次在大规模三维物理相似模拟中,采用基于逆Wishart概率密度函数的自适应卡尔曼滤波数据处理方法,解决了过程和测量噪声不准确的问题,为研究气体运移规律和确定气体运移机理奠定了基础。
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引用次数: 0
Research on robust adaptive sliding film fault-tolerant control under nonlinear distortion of signal transmission in amorphous flat air-to-ground wireless ad-hoc network system 非晶平面空对地无线自组网系统信号传输非线性失真下的鲁棒自适应滑动膜容错控制研究
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2022-01-03 DOI: 10.1108/aa-04-2021-0045
Zhifang Wang, Jianguo Yu, Shangjing Lin
PurposeTo solve the above problems and ensure the stability of the ad hoc network node topology in the process of wireless signal transmission, this paper aims to design a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.Design/methodology/approachThis paper designs a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.FindingsThe simulation results show that the amorphous flat wireless self-organizing network system has good nonlinear distortion fault-tolerant correction ability under the feedback control of the designed controller, and the system has the asymptotically stable convergence ability; the test results show: the node topology of the self-organizing network structural stability is significantly improved, which provides a foundation for the subsequent realization of long-distance transmission of ad hoc network nodes.Research limitations/implicationsBecause of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.Originality/valueThe controller can extract the fault information caused by nonlinear distortion in the wireless signal transmission process, and at the same time, its feedback matrix K can gradually converge the generated wireless signal error to zero, to realize the stable transmission of the wireless signal.
目的为了解决上述问题,确保无线信号传输过程中自组织网络节点拓扑结构的稳定性,本文旨在设计一种在无定形平面空地无线自组织网络系统中,在信号传输非线性失真情况下的鲁棒自适应滑膜容错控制器。设计/方法/途径本文设计了一种在无定形平面空对地无线自组织网络系统中信号传输非线性失真情况下的鲁棒自适应滑动膜容错控制器。仿真结果表明,在所设计控制器的反馈控制下,非晶平面无线自组织网络系统具有良好的非线性失真容错校正能力,系统具有渐近稳定的收敛能力;测试结果表明:自组织网络的节点拓扑结构稳定性显著提高,为后续实现adhoc网络节点的远程传输奠定了基础。研究局限性/含义由于所选择的研究方法,研究结果可能缺乏可推广性。因此,鼓励研究人员进一步检验所提出的命题。独创性/价值控制器可以提取无线信号传输过程中非线性失真引起的故障信息,同时其反馈矩阵K可以将生成的无线信号误差逐渐收敛为零,实现无线信号的稳定传输。
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引用次数: 2
期刊
Assembly Automation
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