Pade-augmented artificial potential field-based cooperative control for multi-Mobile robot transportation systems...

Area of Science:

• Robotics
• Control Systems Engineering
• Artificial Intelligence

Background:

• Cooperative transportation with multi-mobile robots (MMRs) faces challenges from input delays, friction, external disturbances, and parameter variations.
• Existing control strategies often struggle to maintain stability and robustness under these complex operating conditions.

Purpose of the Study:

• To develop a distributed leader-follower cooperative control strategy for MMRs that enhances stability and robustness.
• To address challenges posed by input delays, frictional forces, external disturbances, and parameter perturbations in MMR systems.

Main Methods:

• A dynamic model of the MMR system was established and transformed into a delay-free form using first-order Pade approximation.
• A fixed-time nonlinear disturbance observer (NDO) was designed to estimate and compensate for lumped disturbances.
• A Pade-augmented artificial potential field (P-APF) controller was developed using equivalent delay state variables for formation convergence and connectivity.

Main Results:

• The proposed controller ensures accurate formation convergence and maintains inter-robot connectivity.
• Asymptotic convergence of the nominal error system was proven using LaSalle's invariance theorem and Barbalat's lemma.
• The actual closed-loop system demonstrated uniformly ultimately bounded formation and velocity errors under bounded residual terms.

Conclusions:

• The Pade-augmented artificial potential field strategy effectively achieves stable cooperative transportation for MMRs.
• The integration of a nonlinear disturbance observer significantly enhances the system's robustness against uncertainties.
• The proposed control approach provides a reliable solution for complex MMR cooperative tasks.