Adaptive robust model predictive control for nonlinear systems
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2019
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| Online Access: | https://hdl.handle.net/1721.1/122395 |
| _version_ | 1826195492277583872 |
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| author | Lopez, Brett Thomas. |
| author2 | Jonathan P. How. |
| author_facet | Jonathan P. How. Lopez, Brett Thomas. |
| author_sort | Lopez, Brett Thomas. |
| collection | MIT |
| description | Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019 |
| first_indexed | 2024-09-23T10:13:57Z |
| format | Thesis |
| id | mit-1721.1/122395 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:13:57Z |
| publishDate | 2019 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1223952019-11-22T03:30:42Z Adaptive robust model predictive control for nonlinear systems Lopez, Brett Thomas. Jonathan P. How. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Aeronautics and Astronautics. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 115-124). Modeling error and external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation by optimizing over control policies but at the expense of computational complexity. An alternative strategy, known as tube MPC, uses a robust controller (designed offline) to keep the system in an invariant tube centered around a desired nominal trajectory (generated online). While tube MPC regains tractability, there are several theoretical and practical problems that must be solved for it to be used in real-world scenarios. First, the decoupled trajectory and control design is inherently suboptimal, especially for systems with changing objectives or operating conditions. Second, no existing tube MPC framework is able to capture state-dependent uncertainty due to the complexity of calculating invariant tubes, resulting in overly-conservative approximations. And third, the inability to reduce state-dependent uncertainty through online parameter adaptation/estimation leads to systematic error in the trajectory design. This thesis aims to address these limitations by developing a computationally tractable nonlinear tube MPC framework that is applicable to a broad class of nonlinear systems. "This work was supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1122374, by the DARPA Fast Lightweight Autonomy (FLA) program, by the NASA Convergent Aeronautics Solutions project Design Environment for Novel Vertical Lift Vehicles (DELIVER), and by ARL DCIST under Cooperative Agreement Number W911NF- 17-2-0181"--Page 7. by Brett T. Lopez. Ph. D. Ph.D. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics 2019-10-04T21:32:05Z 2019-10-04T21:32:05Z 2019 2019 Thesis https://hdl.handle.net/1721.1/122395 1119667757 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 124 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Aeronautics and Astronautics. Lopez, Brett Thomas. Adaptive robust model predictive control for nonlinear systems |
| title | Adaptive robust model predictive control for nonlinear systems |
| title_full | Adaptive robust model predictive control for nonlinear systems |
| title_fullStr | Adaptive robust model predictive control for nonlinear systems |
| title_full_unstemmed | Adaptive robust model predictive control for nonlinear systems |
| title_short | Adaptive robust model predictive control for nonlinear systems |
| title_sort | adaptive robust model predictive control for nonlinear systems |
| topic | Aeronautics and Astronautics. |
| url | https://hdl.handle.net/1721.1/122395 |
| work_keys_str_mv | AT lopezbrettthomas adaptiverobustmodelpredictivecontrolfornonlinearsystems |