LAPSE:2020.1228
Published Article

LAPSE:2020.1228
Online High Performance Genetic Algorithm Based Sliding Mode Control for Controllable Pitch Propeller
December 17, 2020
During the voyage of a ship, the performance of a controllable pitch propeller (CPP) is severely affected by the changing load demand and ever-present disturbance from ocean waves, which will also result in model uncertainty. In order to improve the performance of the CPP system, an online high-performance genetic algorithm (HPGA)-based sliding mode control (SMC) strategy is proposed. Firstly, the model of the CPP system is obtained according to the manufacturer’s instructions. Then, a chattering-free sliding mode controller (CF-SMC) is designed for the CPP system, after which the parameters in the CF-SMC are optimized with the HPGA method. Finally, the optimized CF-SMC is applied to an experimental setup of a prototype CPP system. In order to validate the effectiveness of the proposed method, it is compared with a proportional-integral-derivative (PID) controller, which is typically applied on real CPP-systems, with results indicating the superiority of the proposed method.
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Keywords
chattering-free, controllable pitch propeller, high-performance genetic algorithm, real-time, sliding mode control
Subject
Suggested Citation
Wang Y, Wang Q, Fu H. Online High Performance Genetic Algorithm Based Sliding Mode Control for Controllable Pitch Propeller. (2020). LAPSE:2020.1228
Author Affiliations
Wang Y: College of Automation, Harbin Engineering University, Harbin 150001, China
Wang Q: College of Automation, Harbin Engineering University, Harbin 150001, China
Fu H: College of Automation, Harbin Engineering University, Harbin 150001, China
Wang Q: College of Automation, Harbin Engineering University, Harbin 150001, China
Fu H: College of Automation, Harbin Engineering University, Harbin 150001, China
Journal Name
Processes
Volume
8
Issue
8
Article Number
E953
Year
2020
Publication Date
2020-08-07
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr8080953, Publication Type: Journal Article
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LAPSE:2020.1228
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https://doi.org/10.3390/pr8080953
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[v1] (Original Submission)
Dec 17, 2020
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Dec 17, 2020
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https://psecommunity.org/LAPSE:2020.1228
Record Owner
Calvin Tsay
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