Adaptive Optimal Control of Space Tether System for Payload Capture via Policy Iteration

Yiting Feng, Ming Zhang, Wenhao Guo, Changqing Wang

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The libration control problem of space tether system(STS) for post-capture of payload is studied. The process of payload capture will cause tether swing and deviation from the nominal position, resulting in the failure of capture mission. Due to unknown inertial parameters after capturing the payload, an adaptive optimal control based on policy iteration is developed to stabilize the uncertain dynamic system in the post-capture phase. By introducing integral reinforcement learning (IRL) scheme, the algebraic Riccati equation (ARE) can be online solved without known dynamics. To avoid computational burden from iteration equations, the online implementation of policy iteration algorithm is provided by the least-squares solution method. Finally, the effectiveness of the algorithm is validated by numerical simulations.

Translated title of the contribution基于策略迭代的空间系绳载荷捕获自适应最优控制
Original languageEnglish
Pages (from-to)560-570
Number of pages11
JournalTransactions of Nanjing University of Aeronautics and Astronautics
Volume38
Issue number4
DOIs
StatePublished - Aug 2021

Keywords

  • Integral reinforcement learning (IRL)
  • Payload capture
  • Policy iteration
  • Space tether system (STS)
  • State feedback

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