Adaptive Control Design for Human Handwriting Process Based on Electromyography Signals
I Khalil Mahmoud, Inès Chihi, Afef Abdelkrim
- 发表年份
- 2020
- 引用次数
- 5
- 访问权限
- 开放获取
摘要
The most used control approaches of hand prosthesis are based on the forearm muscle activities, named ElectroMyoGraphy signal (EMG). In this sense, researchers modeled the hand writing on the plane only from two EMG signals. Based on this analysis, we can consider the hand as a robot with two arms (two degrees of freedom) moving on ( x , y ) plane. However, these signals are very sensitive to many disturbances and are generally unpredictable in time, type, and level. Based on forearm EMG signals, this work aims to propose an adaptive hand-robot control design to generate handwriting. As a first step, we develop the application of the classic proportional integral structure (PI). The PI controller was applied to generate different essays of handwritten graphic traces in one-writer case and multiwriter case. Both cases have presented unsatisfactory results in generating cursive letters and forms. Indeed, we propose, as a second approach, an adaptive PI controller with varying Integral K i gain, according to EMG signals, in order to deal with operation changes.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991