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Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications最新文献

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Frequency Response Analysis of Macro-Micro Stages With Active Disturbance Reject Controller 采用自抗扰控制器的宏微级频响分析
Zeng Danping, Huang Ruirui, Yang Zhijun, Wenchao Xue
Under the disturbance of friction and the elastic deformation of motion stage, the positioning accuracy of traditional mechanical bearing high speed direct-drive motion stage can only reach the micron level, which is difficult to meet the requirement of higher speed precision positioning. Therefore, the macro-micro stages utilize the flexure hinges to compensate for displacement in the friction dead zone. However, due to the nonlinear elastic vibration of the flexure hinge during the action, the settling time of micro-platform is different with stiffnesses. Effect analysis of different stiffness on the settling time of the micro-platform is significant for the platform design. According to the motion characteristics of the macro-micro stages, this paper designs the cascade extended state observer (ESO) to estimate and compensate for the disturbance and combine the proportional–derivative (PD) controller as the active disturbance rejection control (ADRC) strategy of the micro-platform position loop. Through the frequency response analysis of the control system, the influence of different stiffness on the settling time of micro-platform is explored. The simulation results show that the ADRC strategy based on cascade ESO has better robustness, and the macro-micro stages have a shorter settling time when the flexure hinge have smaller stiffness during the positioning phase.
传统机械轴承高速直驱式运动平台在摩擦力和运动平台弹性变形的扰动下,定位精度只能达到微米级,难以满足更高速度精度定位的要求。因此,宏观-微观阶段利用柔性铰链来补偿摩擦死区的位移。然而,由于柔性铰链在作用过程中的非线性弹性振动,微平台的沉降时间随刚度的不同而不同。分析不同刚度对微平台沉降时间的影响对微平台设计具有重要意义。针对微平台位置环的宏观和微观运动特点,设计了串级扩展状态观测器(ESO)来估计和补偿扰动,并结合比例导数(PD)控制器作为微平台位置环的自抗扰控制策略。通过对控制系统的频响分析,探讨了不同刚度对微平台沉降时间的影响。仿真结果表明,基于级联ESO的自抗扰策略具有较好的鲁棒性,且当柔性铰链在定位阶段刚度较小时,宏微观阶段的沉降时间较短。
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引用次数: 0
Heuristic Approach for Warehouse Resources and Production Planning Optimization: An Industry Case Study 仓库资源和生产计划优化的启发式方法:一个行业案例研究
Roberto Rosetti, M. Sturari, E. Frontoni, J. Loncarski, A. Cicchitti, Enrico Iavazzo, D. Gualtieri
Industrial sector for production of manufacturing machinery and equipment is a very competitive and difficult market to deal with. Difficulties increase in areas that involves the design, manufacturing and assembly of large production machines. In fact, in this case the effort to produce a single item is much bigger in time, money and resources with respect to other areas. Long time for production paired with a not accurate usage of internal resources can produce a large number of unused components and semi-finished products. This paper presents a real case study of a company leader in the designing and manufacturing machinery for disposable hygienic products and highly automated liquid filling integrated systems. Each product is a huge assembly of components and semi-finished products and many of them are not used for production even if they are stored in company’s warehouses. This is due to the logistic and human factors that can be managed and corrected. In this paper a math-heuristic approach for warehouse resources and components procurement optimization is presented. A real instance related to a commission has been solved and results are presented and analyzed.
工业部门生产制造机械设备是一个竞争非常激烈的市场,很难应对。在涉及大型生产机器的设计、制造和组装的领域,困难增加了。事实上,在这种情况下,与其他领域相比,制作一件物品的时间、金钱和资源要大得多。生产时间长,加上内部资源利用不准确,会产生大量未使用的零部件和半成品。本文介绍了一家在一次性卫生用品和高度自动化液体灌装集成系统的设计和制造机械方面处于领先地位的公司的真实案例研究。每个产品都是一个巨大的组件和半成品的组装,其中许多产品即使存放在公司的仓库中也不会用于生产。这是由于可以管理和纠正的物流和人为因素。本文提出了一种仓库资源和零部件采购优化的数学启发式方法。通过实例分析,给出了求解结果。
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引用次数: 0
Computer Vision-Based Object Recognition and Automatic Pneumatic Soft Gripping 基于计算机视觉的物体识别与自动气动软夹持
Ebrahim Shahabi, Weihao Lu, P. Lin, C. Kuo
During recent years, soft robotic is a new sub-class of the robots. Soft robotic has several engaging features, such as lightweight, low cost, simple fabrication, easy control, etc. Commercial products such as soft grippers are now available to apply in various fields and applications, for example, agriculture, medicine, machinery, etc. This paper proposes a novel method of grasping in soft robotic fields using computer vision to find the shape, size, and angle of the object to define the best type of grasping mode. Random Sample Consensus (RANSAC) was used to iteratively select randomly sampled 3D points to determine the working plane and identify the randomly placed object. Furthermore, we designed and fabricated a 3D-printed pneumatic soft actuator. The ratio of payload over weight is around 16. Experiments showed the proposed computer vision techniques and pneumatic soft gripper are capable of automatically recognize the object shape and perform soft gripping.
软机器人是近年来发展起来的一个新的机器人分支。软机器人具有重量轻、成本低、制造简单、易于控制等特点。商业产品,如软夹持器,现在可应用于各个领域和应用,如农业,医药,机械等。本文提出了一种新的软机器人抓取方法,利用计算机视觉来寻找物体的形状、大小和角度,以确定最佳抓取方式。采用随机样本一致性(RANSAC)算法迭代选择随机采样的三维点来确定工作平面和识别随机放置的物体。此外,我们还设计并制作了一个3d打印气动软执行器。有效载荷与重量之比约为16。实验表明,所提出的计算机视觉技术和气动软夹持器能够自动识别物体形状并进行软夹持。
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引用次数: 0
An Event Based Machine Learning Framework for Predictive Maintenance in Industry 4.0 工业4.0中基于事件的预测性维护机器学习框架
Matteo Calabrese, Martin Cimmino, Martina Manfrin, F. Fiume, D. Kapetis, M. Mengoni, S. Ceccacci, E. Frontoni, M. Paolanti, Alberto Carrotta, G. Toscano
Predictive Maintenance concerns the smart monitoring of machine to avoid possible future failures, since because it is better to intervene before the damage occurs, saving time and money. In this paper, a Predictive Maintenance methodology based on Machine learning approach is presented and it is applied to a real cutting machine, a woodworking machinery in a real industrial group, producing accurate estimations. This kind of strategy is important to deal with maintenance problems given the ever increasing need to reduce downtime and associated costs. The Predictive Maintenance methodology implemented allows dynamical decision rules that have to be considered for maintenance prediction using a combined approach on Azure Machine Learning Studio. The Three models (RF, GBM and XGBM) allowed the accurately predict machine down ever gripped bearing thanks to the pre-processing phases.
预测性维护关注的是机器的智能监控,以避免未来可能出现的故障,因为最好在损坏发生之前进行干预,从而节省时间和金钱。本文提出了一种基于机器学习方法的预测性维护方法,并将其应用于实际工业集团中的切割机、木工机械,产生了准确的估计。考虑到不断增加的减少停机时间和相关成本的需求,这种策略对于处理维护问题非常重要。实现的预测性维护方法允许使用Azure Machine Learning Studio的组合方法进行维护预测时必须考虑的动态决策规则。由于预处理阶段,三个模型(RF, GBM和XGBM)可以准确预测机器的下夹持轴承。
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引用次数: 8
Low-Cost Real-Time Vision Platform for Spatial Temperature Control Research Education Developments 空间温度控制研究教育发展的低成本实时视觉平台
J. Viola, Alberto Radici, Sina Dehghan, Y. Chen
Temperature control is present in many industrial processes, making this skill mandatory for the control engineers. For this reason, different training temperature platforms have been created for this purpose. However, many of these platforms are expensive, require elaborate facility accommodations, and have higher heating and cooling times, making not suitable for teaching and training. This paper presents a low-cost educational platform for temperature control training. The platform employs a Peltier module as a heating element, which has lower heating and cooling time than other thermal system implementations. A low-cost real-time thermal camera is employed as a temperature feedback sensor instead of a standard thermal sensor. The control algorithm is developed in Matlab-Simulink and employs an Arduino board as hardware in the loop to manage the Peltier module. A temperature control experiment is performed to show that the platform is suitable for teaching and training experiences not only in the classroom but for engineers in the industry.
温度控制存在于许多工业过程中,因此控制工程师必须具备这一技能。为此,我们创建了不同的训练温度平台。然而,许多此类平台价格昂贵,需要精心设计的设施住宿,并且加热和冷却时间较长,因此不适合教学和培训。本文提出了一种低成本的温控培训教学平台。该平台采用Peltier模块作为加热元件,与其他热系统相比,加热和冷却时间更短。采用低成本实时热像仪作为温度反馈传感器代替标准热传感器。控制算法在Matlab-Simulink中开发,采用Arduino板作为环内硬件来管理Peltier模块。通过温度控制实验表明,该平台不仅适用于课堂教学和培训,也适用于工业工程师的教学和培训。
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引用次数: 4
Fire Detection Using Both Infrared and Visual Images With Application to Unmanned Aerial Vehicle Forest Fire Surveillance 基于红外和视觉图像的火灾探测及其在无人机森林火灾监视中的应用
C. Yuan, Zhixiang Liu, Anim Hossain, Youmin Zhang
Forest fires are a universal problem that destroy a large amount of natural resources and creates environmental pollution. Forest firefighting is one of today’s most important events for natural and environmental resources protection and conservation. Unmanned aerial vehicle (UAV) with remote sensing system can offer a rapid, safe and low-cost approach for effective forest fire detection which have attracted researchers attention worldwide. In this paper, automatic detection of fire regions using both visual and infrared images is investigated. In order to improve the computational performance to satisfy the requirement of real-time processing, a reduced complexity fusion method is adopted in this research. Through testing the proposed approach on real video sequences, good detection performance is achieved and it is indicated that using multi-modal camera system to detect forest fire with application to firefighting UAV is very promising.
森林火灾是一个全球性的问题,它破坏了大量的自然资源,造成了环境污染。森林消防是当今保护和节约自然环境资源的重要活动之一。具有遥感系统的无人机为森林火灾的有效探测提供了一种快速、安全、低成本的方法,引起了国内外研究者的广泛关注。本文研究了利用视觉和红外图像对火灾区域进行自动检测的方法。为了提高计算性能以满足实时处理的要求,本研究采用了一种降低复杂度的融合方法。通过对真实视频序列的测试,该方法取得了良好的检测性能,表明将多模态摄像机系统用于森林火灾检测并应用于消防无人机是很有前景的。
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引用次数: 2
Fractional-Order Extreme Learning Machine With Mittag-Leffler Distribution 具有Mittag-Leffler分布的分数阶极限学习机
Haoyu Niu, Yuquan Chen, Yangquan Chen
Extreme Learning Machine (ELM) has a powerful capability to approximate the regression and classification problems for a lot of data. ELM does not need to learn parameters in hidden neurons, which enables ELM to learn a thousand times faster than conventional popular learning algorithms. Since the parameters in the hidden layers are randomly generated, what is the optimal randomness? Lévy distribution, a heavy-tailed distribution, has been shown to be the optimal randomness in an unknown environment for finding some targets. Thus, Lévy distribution is used to generate the parameters in the hidden layers (more likely to reach the optimal parameters) and better computational results are then derived. Since Lévy distribution is a special case of Mittag-Leffler distribution, in this paper, the Mittag-Leffler distribution is used in order to get better performance. We show the procedure of generating the Mittag-Leffler distribution and then the training algorithm using Mittag-Leffler distribution is given. The experimental result shows that the Mittag-Leffler distribution performs similarly as the Lévy distribution, both can reach better performance than the conventional method. Some detailed discussions are finally presented to explain the experimental results.
极限学习机(ELM)对大量数据的回归和分类问题具有强大的逼近能力。ELM不需要学习隐藏神经元中的参数,这使得ELM的学习速度比传统的流行学习算法快1000倍。由于隐藏层中的参数是随机生成的,那么最优的随机性是什么呢?lsamvy分布是一种重尾分布,已被证明是在未知环境中寻找目标的最优随机性。因此,使用lsamvy分布生成隐藏层中的参数(更有可能达到最优参数),从而得到更好的计算结果。由于lsamvy分布是Mittag-Leffler分布的一种特例,因此为了获得更好的性能,本文采用了Mittag-Leffler分布。首先给出了Mittag-Leffler分布的生成过程,然后给出了基于Mittag-Leffler分布的训练算法。实验结果表明,Mittag-Leffler分布与lsamvy分布具有相似的性能,都能达到比传统方法更好的性能。最后对实验结果进行了详细的讨论。
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引用次数: 2
Development of a Compact and Cost Effective MSL System Based on a Compliant Nanomanipulator 基于柔性纳米机械臂的紧凑、低成本MSL系统的研制
Zheng Liu, Zhen Zhang, Y. Guan
This paper proposes a compact and cost-effective MSL (Micro Stereo Lithography) prototyping system. A self-developed compliant XY nanomanipulating stage is responsible for the fabrication quality in one layer. And a blu-ray LED laser module is utilized as a cost-effective light source. The experimental results show that the MSL prototyping system is capable of achieving ∼ 2 μm cured width for circular patterns.
提出了一种结构紧凑、性价比高的微型立体光刻样机系统。自行研制的柔性XY纳米操纵工作台负责一层的制造质量。蓝光LED激光模组是一种经济高效的光源。实验结果表明,MSL原型系统能够实现~ 2 μm的圆形图案固化宽度。
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引用次数: 1
A Modular Approach to Level Curve Tracking With Two Nonholonomic Mobile Robots 两个非完整移动机器人水平曲线跟踪的模块化方法
Sarthak Chatterjee, Wencen Wu
In this paper, we consider the problem of tracking noisy two-dimensional level curves using only the instantaneous measurements of the field, taken by two mobile agents, without the need of estimating the field gradient. To do this, we propose a dual-control-module structure consisting of the formation control and curve tracking modules. The former uses the linear velocity of the agents to generate the angular velocities, which are then used to maintain a constant distance between the two agents. The latter uses the instantaneous field measurements to generate the linear velocities of the two agents to successfully track level curves. The modular approach decouples the problems of formation control and curve tracking, thus allowing the seamless design of the two modules. We show that the proposed dual-module control structure allows fast and accurate tracking of planar level curves.
在本文中,我们考虑了在不需要估计场梯度的情况下,仅使用两个移动代理对场的瞬时测量来跟踪有噪声的二维水平曲线的问题。为此,我们提出了由地层控制和曲线跟踪模块组成的双控制模块结构。前者使用agent的线速度来生成角速度,然后使用角速度来保持两个agent之间的恒定距离。后者使用瞬时场测量来生成两个代理的线速度,以成功地跟踪水平曲线。模块化方法将地层控制和曲线跟踪问题解耦,从而实现两个模块的无缝设计。结果表明,所提出的双模块控制结构可以快速准确地跟踪平面水平曲线。
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引用次数: 2
Development of an Assist-As-Need Controller for an Upper-Limb Exoskeleton With Voluntary Torque Estimate 具有自动扭矩估计的上肢外骨骼随需辅助控制器的研制
Logan T. Chatfield, Benjamin C. Fortune, Lachlan R. McKenzie, C. Pretty
This study considers the development of an assist-as-need torque controller for an exoskeleton for stroke rehabilitation. Studies have shown that active patient participation improves the patient’s recovery from stroke. Assist-as-need control, providing the patient with the assistance they need to complete a task, is desirable, as the assistance can be varied to maximise patient participation. However, research is limited, and current methods cannot guarantee optimal assistance as non-zero assistive forces are still provided to subjects that are capable of completing the task unassisted. This study proposes a control system to vary and optimise the assistance for a subject based on their capabilities. A particle filter developed from previous research is used to estimate the subject’s voluntary effort. The assistive torque is determined from a target torque and the voluntary effort. The controller is shown to be effective, as zero assistance is provided to a subject capable of completing the task unassisted. Additionally, the assistance will increase if the subject fatigues. Using the estimate of the subject’s strength, the assistive torque can be accurately set to maximise a patient’s participation, and therefore, the assist-as-need controller can lead to improved therapeutic results.
本研究考虑开发一种用于中风康复外骨骼的按需辅助扭矩控制器。研究表明,患者积极参与有助于中风患者的康复。按需协助控制,为患者提供他们完成任务所需的帮助,是可取的,因为帮助可以多种多样,以最大限度地提高患者的参与。然而,研究是有限的,目前的方法不能保证最优的辅助,因为非零辅助力仍然提供给能够独立完成任务的受试者。本研究提出了一个控制系统,根据受试者的能力来改变和优化他们的帮助。在前人的研究基础上,提出了一种粒子滤波方法来估计受试者的自愿努力。辅助扭矩由目标扭矩和自主力确定。控制器被证明是有效的,因为对于能够独立完成任务的受试者,控制器不会提供任何帮助。此外,如果受试者疲劳,援助会增加。通过对受试者力量的估计,可以准确地设置辅助扭矩,以最大限度地提高患者的参与程度,因此,按需辅助控制器可以改善治疗效果。
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引用次数: 5
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Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications
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