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.
{"title":"Heuristic Approach for Warehouse Resources and Production Planning Optimization: An Industry Case Study","authors":"Roberto Rosetti, M. Sturari, E. Frontoni, J. Loncarski, A. Cicchitti, Enrico Iavazzo, D. Gualtieri","doi":"10.1115/detc2019-97768","DOIUrl":"https://doi.org/10.1115/detc2019-97768","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114923438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote sensing and aerial imaging efforts at University of Maryland Eastern Shore (UMES) have been ongoing for over a decade. It was initiated with the UMESAIR (Undergraduate Multidisciplinary Earth Science Airborne Instrumentation Research) project in early part of the century as an exploratory experiential learning project as means to foster collaboration and provide exposure to science and engineering students to scientists and engineers at NASA’s Wallops Flight Facility which is within 50 miles of campus. Subsequently, with significant support from USDA’s National Institute of Food and Agriculture (NIFA) the remote sensing endeavors have been integrated with the smart farming and precision agriculture efforts closely aligned with the land grant mission of UMES and the regional emphasis in the Delmarva Peninsula. Maryland Space Grant Consortium (MDSGC) have also supported a synergistic project titled Aerial Imaging and Remote Sensing for Precision Agriculture and Environmental Stewardship (AIRSPACES) on an annual basis which has allowed continued involvement of multidisciplinary undergraduate students from the STEM fields to remain involved with the efforts.
马里兰大学东岸分校(University of Maryland Eastern Shore)的遥感和航空成像工作已经进行了十多年。它是在本世纪初与UMESAIR(本科多学科地球科学机载仪器研究)项目一起启动的，作为一个探索性的体验式学习项目，作为促进合作的手段，并为科学和工程专业的学生提供接触NASA沃洛普斯飞行设施的科学家和工程师的机会，该设施距离校园不到50英里。随后，在美国农业部国家粮食和农业研究所(NIFA)的大力支持下，遥感工作已与智能农业和精准农业工作相结合，与美国农业科学研究所的土地赠款任务和德尔马瓦半岛的区域重点密切相关。马里兰空间资助联盟(MDSGC)还每年支持一项名为“精确农业和环境管理航空成像和遥感”(AIRSPACES)的协同项目，该项目允许来自STEM领域的多学科本科生继续参与这项工作。
{"title":"Overview of Remote Sensing Efforts at University of Maryland Eastern Shore","authors":"A. Nagchaudhuri, Travis Ford, C. Hartman","doi":"10.1115/detc2019-98457","DOIUrl":"https://doi.org/10.1115/detc2019-98457","url":null,"abstract":"\u0000 Remote sensing and aerial imaging efforts at University of Maryland Eastern Shore (UMES) have been ongoing for over a decade. It was initiated with the UMESAIR (Undergraduate Multidisciplinary Earth Science Airborne Instrumentation Research) project in early part of the century as an exploratory experiential learning project as means to foster collaboration and provide exposure to science and engineering students to scientists and engineers at NASA’s Wallops Flight Facility which is within 50 miles of campus. Subsequently, with significant support from USDA’s National Institute of Food and Agriculture (NIFA) the remote sensing endeavors have been integrated with the smart farming and precision agriculture efforts closely aligned with the land grant mission of UMES and the regional emphasis in the Delmarva Peninsula. Maryland Space Grant Consortium (MDSGC) have also supported a synergistic project titled Aerial Imaging and Remote Sensing for Precision Agriculture and Environmental Stewardship (AIRSPACES) on an annual basis which has allowed continued involvement of multidisciplinary undergraduate students from the STEM fields to remain involved with the efforts.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116722967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Frequency Response Analysis of Macro-Micro Stages With Active Disturbance Reject Controller","authors":"Zeng Danping, Huang Ruirui, Yang Zhijun, Wenchao Xue","doi":"10.1115/detc2019-98352","DOIUrl":"https://doi.org/10.1115/detc2019-98352","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129540059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"An Event Based Machine Learning Framework for Predictive Maintenance in Industry 4.0","authors":"Matteo Calabrese, Martin Cimmino, Martina Manfrin, F. Fiume, D. Kapetis, M. Mengoni, S. Ceccacci, E. Frontoni, M. Paolanti, Alberto Carrotta, G. Toscano","doi":"10.1115/detc2019-97917","DOIUrl":"https://doi.org/10.1115/detc2019-97917","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133324719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Low-Cost Real-Time Vision Platform for Spatial Temperature Control Research Education Developments","authors":"J. Viola, Alberto Radici, Sina Dehghan, Y. Chen","doi":"10.1115/detc2019-97664","DOIUrl":"https://doi.org/10.1115/detc2019-97664","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122341874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Fire Detection Using Both Infrared and Visual Images With Application to Unmanned Aerial Vehicle Forest Fire Surveillance","authors":"C. Yuan, Zhixiang Liu, Anim Hossain, Youmin Zhang","doi":"10.1115/detc2019-97895","DOIUrl":"https://doi.org/10.1115/detc2019-97895","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128851554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Fractional-Order Extreme Learning Machine With Mittag-Leffler Distribution","authors":"Haoyu Niu, Yuquan Chen, Yangquan Chen","doi":"10.1115/detc2019-97652","DOIUrl":"https://doi.org/10.1115/detc2019-97652","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114369484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Development of a Compact and Cost Effective MSL System Based on a Compliant Nanomanipulator","authors":"Zheng Liu, Zhen Zhang, Y. Guan","doi":"10.1115/detc2019-97522","DOIUrl":"https://doi.org/10.1115/detc2019-97522","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128815560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"A Modular Approach to Level Curve Tracking With Two Nonholonomic Mobile Robots","authors":"Sarthak Chatterjee, Wencen Wu","doi":"10.1115/detc2019-97665","DOIUrl":"https://doi.org/10.1115/detc2019-97665","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126234769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Development of an Assist-As-Need Controller for an Upper-Limb Exoskeleton With Voluntary Torque Estimate","authors":"Logan T. Chatfield, Benjamin C. Fortune, Lachlan R. McKenzie, C. Pretty","doi":"10.1115/detc2019-98297","DOIUrl":"https://doi.org/10.1115/detc2019-98297","url":null,"abstract":"\u0000 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.","PeriodicalId":166402,"journal":{"name":"Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121133562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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