Approximation-free Control of Unknown Euler-Lagrangian Systems under Input Constraints

In this paper, we present a novel funnel-based tracking control algorithm for robotic systems with unknown dynamics and prescribed input constraints. The Euler-Lagrange formulation, a common modeling approach for robotic systems, has been adopted in this study to address the trade-off between performance and actuator safety. We establish feasibility conditions that ensure tracking errors evolve within predefined funnel bounds while maintaining bounded control efforts, a crucial consideration for robots with limited actuation capabilities. We propose two approximation-free control strategies for scenarios where these conditions are violated: one actively corrects the error, and the other stops further deviation. Finally, we demonstrate the robust performance and safety of the approach through simulations and experimental validations. This work represents a significant advancement in funnel-based control, enhancing its applicability to real-world robotics systems with input constraints.

@article{das2025_2507.01426,
  title={ Approximation-free Control of Unknown Euler-Lagrangian Systems under Input Constraints },
  author={ Ratnangshu Das and Pushpak Jagtap },
  journal={arXiv preprint arXiv:2507.01426},
  year={ 2025 }
}