Nonlinear Intelligent Control of Two Link Robot Arm by Considering Human Voluntary Components

Area of Science:

• Robotics
• Biomechanics
• Intelligent Control Systems

Background:

• Human arm viscoelastic properties (joint stiffness and viscosity) are regulated differently based on task requirements.
• Previous research on human arm viscoelasticity often filtered out motor commands, omitting voluntary dynamics.
• Understanding and modeling human voluntary components is crucial for advancing robotics, rehabilitation, and sports technologies.

Purpose of the Study:

• To develop a nonlinear intelligent control strategy for a two-link robot arm.
• To incorporate human voluntary components into the robot arm control model.
• To improve the accuracy and applicability of robot arm control by considering human motor dynamics.

Main Methods:

• A model of the human multi-joint arm was obtained by considering human voluntary components.
• Support Vector Regression (SVR) technique was employed to learn the human arm model.
• A nonlinear intelligent control strategy was designed based on the learned human arm model.

Main Results:

• The study successfully modeled human voluntary components in arm movements using SVR.
• A nonlinear intelligent control system for a two-link robot arm was proposed and implemented.
• Experimental results validated the effectiveness of the proposed control strategy.

Conclusions:

• The proposed nonlinear intelligent control effectively incorporates human voluntary components.
• The approach enhances robot arm control by considering human motor dynamics.
• This research contributes to the development of more sophisticated robots for industrial, rehabilitation, and sports applications.