Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System

Ines Chihi,Mohamed Benrejeb

doi:10.1155/2018/9789060

Ines Chihi, Mohamed Benrejeb

Open Access

https://doi.org/10.1155/2018/9789060

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Abstract

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.

Highlights

In the last decades, robot control is considered as an important research field, especially for robots intervening in the tasks of everyday life
The most used control approach is based on the amplifier electrical activity of the muscles, named electromyographic signal (EMG), which allows directly encoding the orders generated by the brain [1,2,3,4]
We propose the new fault detection approach introduced in Figure 4, based on predictive model using parametric identification model for the reconstruction of not healthy inputs (IEMG signals) of the handwriting assistance system using the writing coordinates on (x, y) plane

Summary

Introduction

Robot control is considered as an important research field, especially for robots intervening in the tasks of everyday life (assistance robots, social robots, service robots, clinical application robots, etc.). The most used control approach is based on the amplifier electrical activity of the muscles, named electromyographic signal (EMG), which allows directly encoding the orders generated by the brain [1,2,3,4]. The wealth of information of these biological signals leads several researches to propose approaches based on the muscular activities control. In [7] EMG signals of ten muscles were used to control an artificial hand with four fingers. In [8], an artificial hand with hydraulically driven multifunction. In this context, different reviews of controlling by electrical muscles activities are proposed in [9,10,11,12]

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