Hierarchical Event-Triggered Systems: Safe Learning of Quasi-Optimal Deadline Policies
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929500395143168 |
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| author | Ong, Pio Mazo Jr., Manuel Ames, Aaron D. |
| author_facet | Ong, Pio Mazo Jr., Manuel Ames, Aaron D. |
| contents | We present a hierarchical architecture to improve the efficiency of event-triggered control (ETC) in reducing resource consumption. This paper considers event-triggered systems generally as an impulsive control system in which the objective is to minimize the number of impulses. Our architecture recognizes that traditional ETC is a greedy strategy towards optimizing average inter-event times and introduces the idea of a deadline policy for the optimization of long-term discounted inter-event times. A lower layer is designed employing event-triggered control to guarantee the satisfaction of control objectives, while a higher layer implements a deadline policy designed with reinforcement learning to improve the discounted inter-event time. We apply this scheme to the control of an orbiting spacecraft, showing superior performance in terms of actuation frequency reduction with respect to a standard (one-layer) ETC while maintaining safety guarantees. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_09812 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Hierarchical Event-Triggered Systems: Safe Learning of Quasi-Optimal Deadline Policies Ong, Pio Mazo Jr., Manuel Ames, Aaron D. Systems and Control Optimization and Control We present a hierarchical architecture to improve the efficiency of event-triggered control (ETC) in reducing resource consumption. This paper considers event-triggered systems generally as an impulsive control system in which the objective is to minimize the number of impulses. Our architecture recognizes that traditional ETC is a greedy strategy towards optimizing average inter-event times and introduces the idea of a deadline policy for the optimization of long-term discounted inter-event times. A lower layer is designed employing event-triggered control to guarantee the satisfaction of control objectives, while a higher layer implements a deadline policy designed with reinforcement learning to improve the discounted inter-event time. We apply this scheme to the control of an orbiting spacecraft, showing superior performance in terms of actuation frequency reduction with respect to a standard (one-layer) ETC while maintaining safety guarantees. |
| title | Hierarchical Event-Triggered Systems: Safe Learning of Quasi-Optimal Deadline Policies |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2409.09812 |