Robust Control of Robotic Manipulator with Prescribed Spatio-temporal and Input constraints

Chidre Shravista Kashyap, Pushpak Jagtap, Jishnu Keshavan

Keywords: Robotic Manipulation, Prescribed Time Control, Robust Adaptive Control

TL;DR: Robust adaptive control framework for unknown dynamics of robotic manipulators subject to exogenous disturbances while adhering to prescribed state, input and temporal constraints

Abstract: Precise tracking of a robotic arm motion subject to exogenous disturbances within a stipulated time is a challenging problem. Existing methods either rely on adaptive laws based on structured parameterizations or disturbance observers, which are sensitive to initial parameter estimates. To mitigate these limitations, we propose a robust adaptive control policy that achieves the prescribed time convergence within predefined bounds while adhering to state and input constraints in the presence of unknown external disturbances. In particular, we formulate filtered errors using time-based generators to prespecify settling time. Design a constraint law to enforce state constraints and impose input limits via a saturation function. Then, an adaptive barrier-function-based controller is synthesized from the filtered errors to achieve prescribed time stability. Moreover, the proposed control framework directly enforces state and input constraints in the control law, avoiding Lyapunov redesign required by barrier Lyapunov function methods and the optimization-based filtering used in control barrier function approaches. Prescribed-time stability of the closed-loop system is rigorously established via Lyapunov analysis. Finally, extensive experiments are conducted on the Franka Robotic arm under various external disturbances to demonstrate the efficacy of the proposed scheme.

Submission Number: 46