Metaheuristic Bio-Inspired Algorithms for Prognostics: Application to On-Board Electromechanical Actuators

Dalla Vedova, Matteo D. L.; BERRI, PIER CARLO; RE, STEFANO

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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.

Titolo:	Metaheuristic Bio-Inspired Algorithms for Prognostics: Application to On-Board Electromechanical Actuators
Autori:	DALLA VEDOVA, MATTEO DAVIDE LORENZO BERRI, PIER CARLO RE, STEFANO
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

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http://hdl.handle.net/11583/2729980

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