2019
DOI: 10.1109/access.2019.2942170
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Optimal Thrust Allocation Strategy of Electric Propulsion Ship Based on Improved Non-Dominated Sorting Genetic Algorithm II

Abstract: The azimuth thruster is widely used in electric propulsion ships due to its excellent performance. The thrust allocation (TA) method of multi-azimuth thruster is the key technology in ship motion control. The purpose of TA is to accurately distribute the thrust and angle of each thruster to provide the vessel the required force and moment. A TA strategy based on the improved non-dominated sorting genetic algorithm II (INSGA-II) is developed in this study. The algorithm introduces the differential mutation oper… Show more

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Cited by 16 publications
(8 citation statements)
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References 23 publications
(31 reference statements)
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“…Step 4: Calculate T cx , T cy , and T cn according to equation (25), equation (27), and equation ( 28), respectively.…”
Section: Implementation Of the New Thrust Allocation Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Step 4: Calculate T cx , T cy , and T cn according to equation (25), equation (27), and equation ( 28), respectively.…”
Section: Implementation Of the New Thrust Allocation Methodsmentioning
confidence: 99%
“…Recently, many intelligent optimization algorithms such as genetic algorithm, 25 bee colony algorithm, 26 particle swarm optimization algorithm, 27 harmony search algorithm, 28 and reinforcement learning algorithm 29 have been used to solve the thrust allocation problem. These methods have no restriction to the objective function and constraints of the optimization problem and can obtain high accuracy solutions easily.…”
Section: Introductionmentioning
confidence: 99%
“…As in [15], [47], [58], [59], conflicting objectives of reducing GHG emission and overall operational cost are considered. Some additional objectives which are included in the cost function are optimizing ESS size, minimization of fuel consumption [39], [45], [46], and minimization of the overall mechanical losses [96]. In addition, to enhance the performance of the local optimization of NSGA-II in the population diversity preservation, an improved NSGA-II algorithm was adopted in [39] by replacing the polynomial variation with difference mutation operators.…”
Section: B Heuristic Algorithmmentioning
confidence: 99%
“…In terms of the ship speed vector and the produced thrust, the ship kinematic performance can be obtained from ( 5) [23].…”
Section: B the Ship Motion Modelmentioning
confidence: 99%