The paper addresses the development of an artificial intelligence algorithm implemented for maximum power point tracking control of a unmanned underwater vehicle. It is shown that this algorithm tracks the optimum operation point and provides fast response even in the presence of faults. The strategy implements the tracking algorithm by using real—time measurements, while providing maximum power to the grid without using online data training. The solution is simulated in the Matlab and Simulink to verify the effectiveness of the proposed approach when fault–free and faulty conditions are considered. The simulation results highlight efficient, intrinsic and passive fault tolerant performances of the algorithm for general unmanned underwater vehicles with low inertia.
Artificial Intelligence Tools for Actuator Fault Diagnosis of an Unmanned Underwater Vehicle / Castaldi P.; Farsoni S.; Menghini M.; Simani S.. - ELETTRONICO. - 507:(2022), pp. 392-403. [10.1007/978-3-031-10464-0_26]
Artificial Intelligence Tools for Actuator Fault Diagnosis of an Unmanned Underwater Vehicle
Castaldi P.Primo
Writing – Original Draft Preparation
;
2022
Abstract
The paper addresses the development of an artificial intelligence algorithm implemented for maximum power point tracking control of a unmanned underwater vehicle. It is shown that this algorithm tracks the optimum operation point and provides fast response even in the presence of faults. The strategy implements the tracking algorithm by using real—time measurements, while providing maximum power to the grid without using online data training. The solution is simulated in the Matlab and Simulink to verify the effectiveness of the proposed approach when fault–free and faulty conditions are considered. The simulation results highlight efficient, intrinsic and passive fault tolerant performances of the algorithm for general unmanned underwater vehicles with low inertia.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
