Augmented Model Predictive Control: A Balance between Satellite Agility and Computation Complexity
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866915960373379072 |
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| author | Wang, Yiming Tissera, Mihindukulasooriya Sheral Crescent Yu, Haihong Foo, Kai Jie Ethan Keyuan, Sean Yeo Srivastava, Ankit An, Hao |
| author_facet | Wang, Yiming Tissera, Mihindukulasooriya Sheral Crescent Yu, Haihong Foo, Kai Jie Ethan Keyuan, Sean Yeo Srivastava, Ankit An, Hao |
| contents | Agile earth observation satellites employ multiple actuators to enable flexible and responsive imaging capabilities. While significant advancements in actuator technology have enhanced satellites' torque and momentum, relatively little attention has been given to control strategies specifically tailored to improve satellite agility. This paper provides a comparative analysis of different Model Predictive Control (MPC) formulations and introduces an augmented-MPC method that effectively balances agility requirements with hardware implementation constraints. The proposed method achieves the high-performance characteristics of nonlinear MPC while preserving the computational simplicity of linear MPC. Numerical simulations and physical experiments are conducted to validate the effectiveness and feasibility of the proposed approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_08078 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Augmented Model Predictive Control: A Balance between Satellite Agility and Computation Complexity Wang, Yiming Tissera, Mihindukulasooriya Sheral Crescent Yu, Haihong Foo, Kai Jie Ethan Keyuan, Sean Yeo Srivastava, Ankit An, Hao Systems and Control Agile earth observation satellites employ multiple actuators to enable flexible and responsive imaging capabilities. While significant advancements in actuator technology have enhanced satellites' torque and momentum, relatively little attention has been given to control strategies specifically tailored to improve satellite agility. This paper provides a comparative analysis of different Model Predictive Control (MPC) formulations and introduces an augmented-MPC method that effectively balances agility requirements with hardware implementation constraints. The proposed method achieves the high-performance characteristics of nonlinear MPC while preserving the computational simplicity of linear MPC. Numerical simulations and physical experiments are conducted to validate the effectiveness and feasibility of the proposed approach. |
| title | Augmented Model Predictive Control: A Balance between Satellite Agility and Computation Complexity |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2603.08078 |