Variable Universe Fuzzy Control of Adjustable Hydraulic Torque Converter Based on Multi-Population Genetic Algorithm

In order to optimize the control method of guide vane opening in an adjustable hydraulic torque converter, this paper presents a variable universe fuzzy control method for servo system of the adjustable hydraulic torque converter based on the multi-population genetic algorithm. This control method g...

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Bibliographic Details
Published in:IEEE access 2019, Vol.7, p.29236-29244
Main Authors: Mingxue, Li, Guolai, Yang, Xiaoqing, Li, Guixiang, Bai
Format: Article
Language:English
Subjects:
Adaptive control
Adjustable hydraulic torque converter
Blades
Control methods
Fuzzy control
Genetic algorithms
guide vane opening
Hydraulic systems
Hydraulics
Mathematical model
multi-population genetic algorithm
Optimization
servo motor
Servocontrol
Servomotors
Torque converters
Universe
variable universe fuzzy control
Velocity control
Wind turbines
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Summary:In order to optimize the control method of guide vane opening in an adjustable hydraulic torque converter, this paper presents a variable universe fuzzy control method for servo system of the adjustable hydraulic torque converter based on the multi-population genetic algorithm. This control method got a kind of adaptive control as optimizing proportional exponential contraction-expansion factors of the current loop with a genetic algorithm, thus transforming the fuzzy variable universe of the current loop. In this method, we designed a variable universe adaptive fuzzy controller with S-function on an adjustable hydraulic torque converter servo system and conducted some simulation experiments. The simulation results showed that the variable universe control based on genetic algorithm improved the anti-interference and robustness of adjustable hydraulic torque converter servo system compared with control methods in the previous literature. This control method could be a desirable way to adjust guide vane opening with the properties of better accuracy, rapidity, and reliability. Thus, the control method we designed will provide an effective, fast, and stable control strategy for the uncertain system with the properties of nonlinearity, strong disturbance, and uncertain time-varying.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2892181