Adaptive Control Design for Human Handwriting Process Based on Electromyography Signals

Abstract

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 Ki gain, according to EMG signals, in order to deal with operation changes.

Automation of a Hybrid Control for Electrohydraulic Servo-Actuators with Residual Dynamics

“…For the control position target, the subsystem (S 1 ) is then defined as in (10), with u p its input signal. When this target is changed to the effort control, the system will be described by the subsystem (S 2 ), where u F is the new input signal to track some forcedesired trajectory.…”

“…Therefore, it is important to choose a nonlinear control method that is reasonably suitable for hydraulic servo systems. A number of investigations have been conducted on feedback linearization techniques [6,7], adaptive control [8][9][10], backstepping control [11][12][13][14][15], sliding mode control [16][17][18][19] and controller design via quantitative feedback theory [20,21]. The objectives of the abovementioned works are oriented to the control of either position or effort.…”