Multi-strategy improved beluga whale optimization algorithm for controller parameters to enhance feed distribution uniformity in crayfish aquaculture boat

•An unmanned feeding boat for crayfish aquaculture was designed.•Analyzed feed distribution uniformity factors and established evaluation index.•Optimized controller via improved BWO algorithm enhanced feeding control performance.•Field tests confirmed the proposed method enhances feed distribution...

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Vydáno v:Computers and electronics in agriculture Ročník 239; s. 110846
Hlavní autoři: He, Yuchi, Wu, Ruimei, Ruan, Jiazheng, Nie, Pengcheng, Ruan, Jiming, Liu, Zhongshou, He, Guoquan, Xiong, Wenxi, Xiong, Aihua
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.12.2025
Témata:
Controller optimization
Distribution uniformity
Feeding speed control
Multi-strategy improved BWO algorithm
Unmanned aquaculture boat
Multi-strategy improved BWO algorithm
Feeding speed control
Distribution uniformity
Controller optimization
Unmanned aquaculture boat
ISSN:0168-1699
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Shrnutí:•An unmanned feeding boat for crayfish aquaculture was designed.•Analyzed feed distribution uniformity factors and established evaluation index.•Optimized controller via improved BWO algorithm enhanced feeding control performance.•Field tests confirmed the proposed method enhances feed distribution uniformity. This study addresses the issue of the uniform distribution of feed in crayfish aquaculture through the design of an unmanned aquaculture boat. By analyzing the motion characteristics of feed particles, key factors influencing distribution uniformity were identified, including feeding location, blade deflection angle, inlet size, feeding plate inclination angle, and feeding speed. Based on the determination of structural parameters, a multi-strategy improved beluga whale optimization (BWO) algorithm was proposed to optimize controller parameters for feeding speed control.‌ Simulation results demonstrate that the system was optimized by improved BWO, achieving a 28.57% reduction in rise time, 26.74% shorter settling time, and 98.11% lower steady-state error compared to the unoptimized system. The maximum deviation under disturbance is maintained at 8.63%, representing a 62.48% improvement over the unoptimized system. The prototype test results demonstrate that the system of improved BWO optimization reduces rise time by 16.28%, stabilization time by 33.98%, and steady-state error by 80.07%, while improving distribution uniformity by 12.79% compared to the unoptimized system. The results show that the improved BWO method for controller parameters optimization enhances feed distribution uniformity.
ISSN:0168-1699
DOI:10.1016/j.compag.2025.110846