Abstract
This paper develops a robust controller for the attitude tracking of time-energy near-optimal angular velocity obtained by the Legendre Pseudospectral method (LPSM). The information of near-optimal reference trajectory is realized offline by employing the LPSM for the nominal spacecraft model, which is without any uncertainties. Then, the proposed robust controller is employed online to track that near-optimal path while compensating for the inertial uncertainties, external disturbances, and noises under input saturation. The robust scheme is developed by combining the finite-time robust non-linear disturbance observer (RNDO) and the adaptive non-singular fast terminal sliding mode control (NSFTSMC). The estimated output of RNDO directly attenuates lumped disturbance of moderate frequency and thus significantly helps in alleviating the chattering problem. Whereas NSFTSMC ensures the finite-time convergence of relative system states, and adaptive law solves the overestimation problem of controller gains while rejecting high-frequency disturbances. The simulation analysis is carried out to validate the proposed strategy.
| Original language | English |
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| Title of host publication | 2020 28th Mediterranean Conference on Control and Automation, MED 2020 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 230-235 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728157429 |
| DOIs | |
| State | Published - Sep 2020 |
| Externally published | Yes |
| Event | 28th Mediterranean Conference on Control and Automation, MED 2020 - Saint-Raphael, France Duration: 15 Sep 2020 → 18 Sep 2020 |
Publication series
| Name | 2020 28th Mediterranean Conference on Control and Automation, MED 2020 |
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Conference
| Conference | 28th Mediterranean Conference on Control and Automation, MED 2020 |
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| Country/Territory | France |
| City | Saint-Raphael |
| Period | 15/09/20 → 18/09/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
ASJC Scopus subject areas
- Control and Systems Engineering
- Control and Optimization
- Modeling and Simulation