Sampling-Aware Multi-Rate Combined Control for an Orbital Manipulator
Ria Vijayan, Marco De Stefano, Christian Ott
AI summary
Problem
The large frequency disparity between high-rate manipulator control and low-rate spacecraft actuation introduces energy leaks and time-delays that compromise the stability of combined control in on-orbit servicing missions.
Approach
The method decouples the high-rate manipulator dynamics from the base and designs a discrete-time PD controller that explicitly compensates for first-order sampling effects using discrete Lyapunov analysis.
Key results
- Novel combined control strategy decoupling high-rate manipulator and low-rate base dynamics
- Sampling-aware discrete PD controller compensating first-order sampling effects
- Stability bounds mapped for a 1-DoF benchmark system
- Validation via multi-DoF simulation and hardware-in-the-loop experiments
Why it matters
Enables stable and efficient on-orbit servicing by preventing low-rate spacecraft actuation from destabilizing high-precision manipulator operations.
Abstract
In on-orbit servicing missions using robotic manipu- lators, certain challenging scenarios require the use of combined control i.e. actuation of spacecraft and the manipulator, to meet mission requirements. The low frequency of the controller of the spacecraft compared to the manipulator can compromise the stability margin of the combined control. In this paper, we first design a combined control strategy to carefully decouple the high-rate manipulator control from the spacecraft’s low-rate control. Second, we design a novel discrete controller accounting for the first-order effects of the servicer’s low sampling rate. This is realized by augmenting a classical proportional-derivative (PD) control scheme. The operational bounds of the discrete controller are first benchmarked on a one-DoF system and further investigated for performance using a multi-DoF orbital manipulator. The results shed light on the regions of enhanced performance in terms of stability and impulse utilization as a measure of efficiency. Simulation results and hardware-in-the- loop experiments are performed to validate the proposed method.