Integrated Adaptive Super-Twisting Sliding Mode and Variable Impedance Control for Collaborative Multi-Robot Manipulation

Abstract

Collaborative and cooperative robotic systems operating in unstructured environments require advanced control strategies that achieve robustness, flexibility, and safe physical interaction. Conventional control methods often struggle to guarantee stability and performance in multi-robot manipulation under disturbances, modelling errors, and dynamic interaction forces. This thesis proposes a unified control framework that integrates robust nonlinear control, adaptive gain tuning, and variable impedance regulation for scalable collaborative multi-manipulator systems.

The framework is built around a proposed task-space sliding mode (SM) controller that uses unit quaternions for orientation tracking. To mitigate chattering and ensure finite-time convergence, nonsingular terminal and super-twisting sliding mode (STSM) techniques are employed. The research is organized into four successive studies that iteratively develop the proposed control framework. First, an admittance-based nonsingular terminal sliding mode (NTSM) controller is introduced for decentralized cooperative manipulation in simulation. Second, an adaptive task-space nonsingular terminal super-twisting sliding mode (NT-STSM) controller is experimentally validated on a 7-DOF Franka Emika manipulator, addressing practical challenges such as chattering, stable parameter tuning, and hardware implementation. Third, impedance control is integrated into the robust controller to form a super-twisting sliding-mode impedance (STSMI) controller, which is extended to multi-manipulator systems for coordinated motion and internal force regulation. Finally, an adaptive super-twisting sliding mode variable impedance control (STSM-VIC) method is proposed, providing real-time modulation of the virtual stiffness, damping, and inertia while ensuring the passivity through Lyapunov-based analysis.

Comparative simulations and hardware experiments demonstrated that the proposed integrated approach significantly improves tracking accuracy, robustness, and interaction safety compared to conventional controllers. Overall, the results established a scalable and experimentally validated control strategy for reliable cooperative manipulation in real-world collaborative robotic systems.