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多星接管目标的分布式近似最优姿态跟踪控制

Translated title of the contribution: Distributed Approximate Optimal Attitude Tracking Control for Taking Over the Target by Multiple Satellites
  • School of Astronautics, Harbin Institute of Technology
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In the on-orbit service missions of attitude takeover control of the failed spacecraft by multiple service satellites, a distributed attitude tracking takeover control policy is proposed based on the method of adaptive dynamic programming (ADP) with unknown inertia matrix and actuator saturation. Firstly, by modeling and analyzing the attitude system, a value function with torque saturation constraint and desired torque compensation is designed. Under the ADP framework, a set of basis functions is used to approximate the optimal value function, and the distributed approximate optimal attitude tracking control strategy is obtained; Then, the filtered linear regression models relevant to inertia parameters and weight parameters are respectively established with angular acceleration information free and according to concurrent learning method, parameter consensus algorithm and off-policy trajectories, the adaptive inertia parameter identification law and the weight update law are designed; Furthermore, the uniformly ultimate boundedness of the attitude tracking errors, the inertia matrix identification errors and weight parameter estimation errors are proved by Lyapunov method; Finally, the simulation results verify the effectiveness of the distributed attitude tracking control method for attitude tracking and inertia matrix identification under the constraint of torque saturation.

Translated title of the contributionDistributed Approximate Optimal Attitude Tracking Control for Taking Over the Target by Multiple Satellites
Original languageChinese (Traditional)
Pages (from-to)2441-2453
Number of pages13
JournalZidonghua Xuebao/Acta Automatica Sinica
Volume51
Issue number11
DOIs
StatePublished - Nov 2025

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