Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System
Many investigators are interested in improving the control strategies of hand prosthesis to make it functional and more convenient to use. The most used control approach is based on the forearm muscles activities, named ‘ElectroMyoGraphic’ (EMG) signal. However, these biological signals are very sen...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/9789060 |
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| _version_ | 1850083738387480576 |
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| author | Ines Chihi Mohamed Benrejeb |
| author_facet | Ines Chihi Mohamed Benrejeb |
| author_sort | Ines Chihi |
| collection | DOAJ |
| description | Many investigators are interested in improving the control strategies of hand prosthesis to make it functional and more convenient to use. The most used control approach is based on the forearm muscles activities, named ‘ElectroMyoGraphic’ (EMG) signal. However, these biological signals are very sensitive to many disturbances and are generally unpredictable in time, type, and level. This leads to inaccurate identification of user intent and threatens the prosthesis control reliability. This paper proposed a real-time fault detection and localization approach applied to handwriting device on the plane. This approach allows connecting inputs (IEMG signals)/outputs (pen tip coordinates) data as a parametric model for Multi-Inputs Multi-Outputs (MIMO) system. The proposed approach is considered as a model-independent abrupt or intermittent fault detection method and as an alternative solution to the unpredictable input observer based techniques, without any observability requirements. This approach allows detecting, in real time, several types of faults in one or two inputs signals and in the same or different instants. Our study is appropriate for many rapidly expanding fields and practices, including biomedical engineering, robotics, and biofeedback therapy or even military applications. |
| format | Article |
| id | doaj-art-61994a907db04dc38870aeb5754e11c9 |
| institution | DOAJ |
| issn | 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-61994a907db04dc38870aeb5754e11c92025-08-20T02:44:13ZengWileyComplexity1099-05262018-01-01201810.1155/2018/97890609789060Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting SystemInes Chihi0Mohamed Benrejeb1Laboratory of Research in Automation (LA.R.A)Laboratory of Research in Automation (LA.R.A)Many investigators are interested in improving the control strategies of hand prosthesis to make it functional and more convenient to use. The most used control approach is based on the forearm muscles activities, named ‘ElectroMyoGraphic’ (EMG) signal. However, these biological signals are very sensitive to many disturbances and are generally unpredictable in time, type, and level. This leads to inaccurate identification of user intent and threatens the prosthesis control reliability. This paper proposed a real-time fault detection and localization approach applied to handwriting device on the plane. This approach allows connecting inputs (IEMG signals)/outputs (pen tip coordinates) data as a parametric model for Multi-Inputs Multi-Outputs (MIMO) system. The proposed approach is considered as a model-independent abrupt or intermittent fault detection method and as an alternative solution to the unpredictable input observer based techniques, without any observability requirements. This approach allows detecting, in real time, several types of faults in one or two inputs signals and in the same or different instants. Our study is appropriate for many rapidly expanding fields and practices, including biomedical engineering, robotics, and biofeedback therapy or even military applications.http://dx.doi.org/10.1155/2018/9789060 |
| spellingShingle | Ines Chihi Mohamed Benrejeb Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System Complexity |
| title | Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System |
| title_full | Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System |
| title_fullStr | Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System |
| title_full_unstemmed | Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System |
| title_short | Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System |
| title_sort | online fault detection approach of unpredictable inputs application to handwriting system |
| url | http://dx.doi.org/10.1155/2018/9789060 |
| work_keys_str_mv | AT ineschihi onlinefaultdetectionapproachofunpredictableinputsapplicationtohandwritingsystem AT mohamedbenrejeb onlinefaultdetectionapproachofunpredictableinputsapplicationtohandwritingsystem |