Metaheuristic bio-inspired algorithms are a growing class of optimization techniques, particularly suitable for the solution of complex, non-linear and multi-modal problems. In the last few years, new metaheuristic algorithms are continuously being developed, each more suitable for a given class of problems. In this paper, the authors analyze the prognostic Fault Detection and Isolation (FDI) process for an electro-mechanical actuator for flight control system, powered by a BLDC trapezoidal motor. Two algorithms are compared: Genetic Algorithm (GA) and Differential Evolution (DE). A high-fidelity reference model (RM), developed in the Matlab-Simulink environment, simulates the real behavior of the system. Taking advantage of a simpler and faster monitoring model (MM), the algorithms try to estimate the health status of the high fidelity model.
Novel Metaheuristic Bio-Inspired Algorithms for Prognostics of Onboard Electromechanical Actuators / Dalla Vedova, Matteo D. L.; Berri, P. C.; Re, S.. - In: INTERNATIONAL JOURNAL OF MECHANICS AND CONTROL. - ISSN 1590-8844. - STAMPA. - 19:2(2018), pp. 95-101.
Titolo: | Novel Metaheuristic Bio-Inspired Algorithms for Prognostics of Onboard Electromechanical Actuators |
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Data di pubblicazione: | 2018 |
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Appare nelle tipologie: | 1.1 Articolo in rivista |
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http://hdl.handle.net/11583/2729976