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Digital framework for metallic subtractive process planning: Liger optimisation case study

Procedia CIRP 2024年 130卷 1358-1363页

作者： João A. Duro Rob Ward Jack Rooke Emily Pickford Rich Bonnell Adam Brown Robin C. Purshouse David Curtis Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK University of Sheffield Advanced Manufacturing Research Centre University of Sheffield Rotherham S60 5TZ UK

Metallic subtractive process planning is challenging. It requires a blend of expert knowledge, experience, and established manufacturing methods. Decision-making in this domain is multifaceted and complex, and this includes the need to satisfy multiple conflicting demands faced by the manufacturing sector today. However, with the evolving landscape of manufacturing, combined with increased adoptions of digital technologies, the traditional rules of thumb are becoming obsolete. In response, this research investigated these decision-making processes within a subset of the digital framework for subtractive process planning. In particular, it has demonstrated that an advanced open-source optimisation tool (Liger) could be integrated with commercial industrial software and applied to a machining case study. The integrated software intelligently executed and automated simulations using advanced optimisation techniques. The outputs are a range of optimised solutions that support manufacturing engineers’ decision-making. One of the major benefits of the open-source software is that it provides an intuitive to use interface suitable for the non-expert in optimisation, offers a varied range of state-of-the-art multi-objective optimisation algorithms, and is capable of incorporating many different third-party types of software, models and simulations. In this paper, the Liger software has been applied to a simple case study to find the best feedrate and depths of cut that simultaneously minimise the cutting force and the time it takes to complete the machining process. The case study demonstrates proof-of-principle results that the optimisation software can be implemented in a wider process planning context with additional digital manufacturing simulation models.

关键词： Machining Process Planning Multi-Objective Optimisation

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Design and locomotion characteristic analysis of a novel tensegrity hopping robot

Design and locomotion characteristic analysis of a novel ten...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Mo, Jixue Gao, Changqing Fang, Hao Yang, Qingkai Peng Cheng Laboratory Department of Strategic and Advanced Interdisciplinary Research Shenzhen518055 China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Beijing Institute of Technology School of Automation Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9798350325706

In consideration of the poor locomotion ability of most traditional tensegrity robot, a novel tensegrity hopping robot powered by push-pull electromagnets was proposed with better locomotivity. It is able to conduct stable consecutive progressing action and turning action through hopping. This paper covers the structural design, theoretical modeling of the robot's hopping process, as well as its self-righting analysis, simulation and experimental verification. The average moving speed and relative moving speed were measured to be 0.334m/s and 0.641 body length/s respectively, which obviously surpass the general moving ability of most traditional tensegrity robot. In addition, the robot was also validated to have good self-righting characteristic for stable consecutive hopping. Thus this robot can be potentially applied for search, rescue, detection, etc. in outdoor and unstructured environment. © 2023 IEEE.

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Design of a Novel Autonomous Docking System With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named 'CourierFish'. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks. © 2023 IEEE.

关键词： Fish

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Ultrafast capturing in-flight objects with reprogrammable working speed ranges

Ultrafast capturing in-flight objects with reprogrammable wo...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yongkang Jiang Xin Tong Zhongqing Sun Yaimiin Zhou Zhipeng Wang Shuo Jiang Zhen Yin Yulong Ding Bin He Yingtian Li Department of Control Science & Engineering Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Shanghai China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In-flight high-speed object capturing is crucial in nature to improve survival and adaptation to the environment, such as the predation of frogs, leopards, and eagles. Despite its ubiquitousness in nature, capturing fast-moving objects is extremely challenging in engineering implementations. In this paper, we report an ultrafast gripper based on tunable bistable structures. Different from current designs which are only suitable for objects with certain speed ranges once the grippers are fabricated, the working range of object speed of the proposed gripper could be reprogrammed by controlling the sensitivity of the structures. We present the design and fabrication of the proposed gripper in detail. A theoretical model is introduced to construct the energy landscape of the structures and the force response of the gripper when programmed to different states. The results show that in the original state, the gripper is capable of capturing a flying table tennis ball with a high speed of 15 m/s in only 6 ms. When the proposed gripper is controlled to the ultra-sensitive state, a flying ball with only 1 m/s could also be captured. This work broadens the frontiers of in-flight capturing design, and we envision broader promising applications.

关键词： Fabrication Sensitivity Sports equipment Force Aerospace electronics Grippers Robotics and automation

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Trust Establishment for the Role-Based Collaborative Multi-Robot systems

Trust Establishment for the Role-Based Collaborative Multi-R...

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IEEE International Conference on systems, Man and Cybernetics

作者： Behzad Akbari Haibin Zhu Ya-Jun Pan Department of Mechanical Engineering Advanced Control and Mechatronics Laboratory Dalhousie University Halifax NS Canada Department of Computer Science and Mathematics Collaborative Systems Laboratory Nipissing University NorthBay ON Canada

Trust evaluation and trust establishment play crucial roles in the management of trust within a multi-agent system. When it comes to collaboration systems, trust becomes directly linked to the specific roles performed by agents. The Role-Based Collaboration (RBC) methodology serves as a framework for assigning roles that facilitate agent collaboration. Within this context, the behavior of an agent with respect to a role is referred to as a process role. This research paper introduces a role engine that incorporates a trust establishment algorithm aimed at identifying optimal and reliable process roles. In our study, we define trust as a continuous value ranging from 0 to 1. To optimize trustworthy process roles, we have developed a consensus-based Gaussian Process Factor Graph (GPFG) tool. Our simulations and experiments validate the feasibility and efficiency of our proposed approach with autonomous robots in unsignalized intersections and narrow hallways.

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An analysis towards integrated control of wastewater collecting and treatment systems

An analysis towards integrated control of wastewater collect...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Iulian Vasiliev Laurentiu Luca Marian Barbu Ramon Vilanova Sergiu Caraman Department of Automation and Electrical Engineering Dunărea de Jos University of Galati Galati Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain

This paper deals with an analysis regarding the effect of Sewer Network operation on the performances of the integrated wastewater collecting and treatment system. The analysis is done by considering various control actions for the output storage tank of the sewer network, comparing a series of performance indicators defined for both subsystems with their “no control” value. Two cases have been considered regarding the control actions for the output storage tank of the sewer network: 1. keeping the output valve at a constant opening and 2. keeping the output valve at the maximum opening possible such as the outflow is limited to a constant value. While the second case did not prove advantageous, the first one showed that lowering the sewer network output valve opening would improve the integrated system performances.

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Sliding Window-based Particle Swarm optimization Algorithm for a Sewer Network

Sliding Window-based Particle Swarm optimization Algorithm f...

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European control Conference (ECC)

This paper deals with the optimization of a sewer network using a Sliding Window-based Particle Swarm optimization (PSO) algorithm. The sewer network corresponds to a city with a population of 250,000 inhabitants, its model being implemented in BSM Sewer. The optimization of the sewer network is done with respect to the amount of the discharged water minimizing this way the environmental impact of the wastewater collecting and transport systems. In the simulations, an influent containing three components was considered: domestic, pluviometric and industrial influent. Daily weather forecast for influent was considered. The control strategy proposed in this paper is based on the calculus of the optimal control actions for each individual tank with respect to the liquid level in that tank. The optimal controls were determined over a 24-hour sliding time window. The optimization algorithm was run over a time horizon of 28 days, during which two events were considered, one of rain and one of storm. As the daily forecast of the influent is not 100% accurate, a disturbed influent was considered to observe if the performance of the algorithm is maintained in this scenario. The simulation results were compared with those obtained in the operating mode “no control” (all control actions set at 100%).

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Model Predictive control of a wastewater treatment process using neural networks

Model Predictive Control of a wastewater treatment process u...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Iulian Vasiliev Irina Luca Larisa Condrachi Laurentiu Luca Marian Barbu Ramon Vilanova Sergiu Caraman Department of Automation and Electrical Engineering Dunărea de Jos University of Galati Galati Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain

This paper deals with the increasing of the operation efficiency of a wastewater treatment plant by reducing the level of pollutant concentration in the effluent. In essence, the main goal is the reduction of the concentration of organic substrate, Model Predictive control algorithm being used for this, considering as a model of the wastewater treatment process a neural network model based on a simplified mathematical model of the 4th order. For the implementation of the control algorithm, two neural networks were trained. In the first version of the neural network, it was considered that all 4 state variables are measurable and in the second version, only the organic substrate was considered measurable. Regarding the training of the two neural networks, good results were obtained in the case of both versions. Instead, the control algorithm gave better results when the second neural network was used (lower values of the substrate, lower variations of the aeration rate, which means a lower cost of operation).

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Experimental Design of Lower-limb Movement Recognition Based on Support Vector Machine 41

Experimental Design of Lower-limb Movement Recognition Based...

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第41届中国控制会议

作者： Wangyang Ge Juan Zhao Feng Wang Chi Xu Zhaohui Yang Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Rehabilitation Union HospitalTongji Medical CollegeHuazhong Univ.Science & Technology School of Engineering Tokyo University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

As a rehabilitation aid,the lower extremity rehabilitation robot usually works together with the patient during the rehabilitation training process,and achieves therapeutic effects by assisting the patient to complete movements within a certain trajectory for *** realize the active training of the rehabilitation robot,the rehabilitation robot needs to be able to recognize the patient's movement intention and cooperate with *** signals contain rich neuromuscular movement information and are often used to extract patients' movement *** this paper,using the principle of human lower extremity force generation,we designed an experiment for lower extremity action recognition of sEMG *** extracting the composition of feature vectors through time-domain feature values,we designed an SVM classifier to achieve the classification of five common lower extremity actions and obtained an average accuracy rate of 90.66% through the experiment,which verified the effectiveness of the experimental design.

关键词： sEMG signal SVM movement recognition lower-limb

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Intelligent Model-Free control for Tendon-Driven Continuum Robotic Arms

Intelligent Model-Free Control for Tendon-Driven Continuum R...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Nima Maghooli Omid Mahdizadeh S. Ali A. Moosavian Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotic and Automated Systems (ARAS) K. N. Toosi University of Technology Tehran Iran

Continuum manipulator modeling is always associated with structured and unstructured uncertainties. Therefore, model-based control system design for this class of robotic systems will be very challenging. On the other hand, the performance quality of model-free controllers is completely dependent on their hyperparameters; they are also very sensitive to the considered trajectory for the system. As a result, using model-free controllers will require setting parameters for different scenarios. In this research, the design of a model-free controller with comparable performance to model-based control strategies is presented. To this end, various parameters are determined online by the gain adjustment system. The research innovation is to use a supervised machine learning method, fuzzy inference system (FIS), to implement the intelligent gain adaptation system to achieve this goal. The Modified Transpose Jacobian (MTJ) performs well in trajectory tracking due to its approximated feedback linearization tool. In addition, the PID controller structure makes it a locally robust control strategy. An adaptive gain adjustment system can greatly increase algorithm potential and establish the capability to follow trajectories in different work points in the system work space. This research aims to improve the performance of the MTJ model-free control strategy in tracking trajectories starting from arbitrary initial conditions in the system work space. This is achieved by the gain adjustment system design using a fuzzy inference system. Both simulation and experimental results reveal the merits of the proposed controller.

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