The Hybrid Position/Force Walking Robot Control Using Extenics Theory and Neutrosophic Logic Decision

Area of Science:

• Robotics
• Control Systems Engineering
• Artificial Intelligence

Background:

• Hexapod walking robots require advanced control for stability and load capacity.
• Existing control methods often struggle to balance kinematic and dynamic properties effectively.

Purpose of the Study:

• To develop and validate a hybrid force/position control system for hexapod robots.
• To integrate Extenics theory and neutrosophic logic for a robust two-stage decision-making algorithm.

Main Methods:

• A two-stage decision-making algorithm combining Extenics theory (offline) and neutrosophic logic with DSmT theory (real-time).
• Separation of control into kinematic (PID regulator) and dynamic (Sliding Mode Control - SMC) phases.
• Implementation of a dynamic switching algorithm to integrate kinematic and dynamic control strategies.

Main Results:

• The hybrid control system demonstrated efficient operation of hexapod robot motors.
• Experimental results closely matched predictions, validating the control method's effectiveness.
• The switching algorithm improved system precision by compensating for dynamic parameters during different walking phases.

Conclusions:

• The proposed hybrid force/position control is effective for hexapod robots.
• The two-stage decision algorithm successfully leverages kinematic and dynamic control methods.
• The switching algorithm offers precise control with minimal impact on system parameters.