Abstract
A self-learning controller which makes quick and successful adaptations to new conditions can considerably benefit autonomous operations of launch vehicles. To provide a model-free, adaptive process for optimal control, approximate dynamic programming has been introduced to aerospace engineering. A widely used structure of approximate dynamic programming for nonlinear systems is heuristic dynamic programming. This paper proposes a new method using incremental models in heuristic dynamic programming to improve the online learning capacity. This method generates an adaptive near-optimal controller online without a priori knowledge of the system dynamics or off-line learning of the system model. A comparison is made between the conventional heuristic dynamic programming algorithm and the incremental model based heuristic dynamic programming algorithm by applying them to an online flight control problem with an unknown nonlinear model. The results demonstrate that the incremental model based heuristic dynamic programming method accelerates online learning, improves the precision, and can deal with a wider range of initial states compared to the conventional heuristic dynamic programming method.
Original language | English |
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Title of host publication | 68th International Astronautical Congress, IAC 2017 |
Subtitle of host publication | Unlocking Imagination, Fostering Innovation and Strengthening Security |
Publisher | International Astronautical Federation, IAF |
Pages | 7154-7164 |
Number of pages | 11 |
Volume | 11 |
ISBN (Print) | 9781510855373 |
Publication status | Published - 1 Jan 2017 |
Event | 68th International Astronautical Congress: Unlocking Imagination, Fostering Innovation and Strengthening Security, IAC 2017: Unlocking Imagination, Fostering Innovation and Strengthening Security - Adelaide, Australia Duration: 25 Sept 2017 → 29 Sept 2017 Conference number: 68 http://www.iafastro.org/events/iac/iac-2017/ |
Conference
Conference | 68th International Astronautical Congress: Unlocking Imagination, Fostering Innovation and Strengthening Security, IAC 2017 |
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Abbreviated title | IAC 2017 |
Country/Territory | Australia |
City | Adelaide |
Period | 25/09/17 → 29/09/17 |
Internet address |
Keywords
- Adaptive flight control
- Heuristic dynamic programming
- Incremental techniques
- Nonlinear control
- Online learning