Sampling-based 3-D Line-of-Sight PWA Model Predictive Control for Autonomous Rendezvous and Docking with a Tumbling Target

TL;DR

This paper introduces a sampling-based PWA MPC approach for autonomous rendezvous and docking with a tumbling target, improving prediction accuracy and computational efficiency in 3-D line-of-sight dynamics.

Contribution

It proposes a novel sampling-based PWA MPC method with reduced on-board computation and a singularity-free strategy for smooth angle crossing in AR&D tasks.

Findings

Demonstrates improved prediction accuracy with sampling-based MPC.

Reduces computational cost and delay in on-board processing.

Successfully achieves 6-DOF pose tracking in numerical simulations.

Abstract

In this paper, a model predictive control (MPC) framework is employed to realize autonomous rendezvous and docking (AR&D) with a tumbling target, using the piecewise affine (PWA) model of the 3-D line-of-sight (LOS) dynamics and Euler attitude dynamics. Consider the error between the predictions obtained by the approximate linear model and the actual states of nonlinear dynamics, a sampling-based PWA MPC is proposed to sample the predictions in the closer neighborhood of the actual states. Besides, novel constructions of constraints are presented to reduce the on-board computation cost and time-delay. Furthermore, a singularity-free strategy is provided to realize crossing the singularity of angle states smoothly. Then, the mission is achieved by continuous 6-DOF pose (position and attitude) tracking of the target's docking port, with the coupling between the position and attitude of the target's docking port is taken into account. Finally, numerical results are presented to demonstrate the above theories.