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EnglishMetaheuristic bio inspired algorithms are a wide class of optimization algorithms, which recently saw a significant growth due to its effectiveness for the solution of complex problems. In this preliminary work, we assess the performance of two of these algorithms-Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)-for the prognostic analysis of an electro-mechanical flight control actuator, powered by a Brushless DC (BLDC) trapezoidal motor. We focus on the first step of the prognostic process, consisting in an early Fault Detection and Identification (FDI); our model-based strategy consists in using an optimization algorithm to approximate the output of the physical system with a computationally light Monitor Model.
Metaheuristic Bio-Inspired Algorithms for Prognostics: Application to On-Board Electromechanical Actuators / Dalla Vedova, Matteo D. L.; Berri, P. C.; Re, S.. - ELETTRONICO. - (2018). ((Intervento presentato al convegno 3rd International Conference on System Reliability and Safety (ICSRS 2018) tenutosi a Barcellona (Spain) nel 24-26/11/2018.
| Titolo: | Metaheuristic Bio-Inspired Algorithms for Prognostics: Application to On-Board Electromechanical Actuators |
| Autori: | |
| Data di pubblicazione: | 2018 |
| Abstract: | Metaheuristic bio inspired algorithms are a wide class of optimization algorithms, which recently... saw a significant growth due to its effectiveness for the solution of complex problems. In this preliminary work, we assess the performance of two of these algorithms-Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)-for the prognostic analysis of an electro-mechanical flight control actuator, powered by a Brushless DC (BLDC) trapezoidal motor. We focus on the first step of the prognostic process, consisting in an early Fault Detection and Identification (FDI); our model-based strategy consists in using an optimization algorithm to approximate the output of the physical system with a computationally light Monitor Model. |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| Final ICSRS_2018 PaperID_S0032.pdf | Paper - Final Version | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
http://hdl.handle.net/11583/2729980
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