基于模糊PID与混合智能优化的深远海养殖网箱升降控制研究OA

In response to the vulnerability of aquaculture net cages to wave-induced impacts under complex deep-and far-sea conditions,this study designs and verifies a lifting control system based on a fuzzy PID controller combined with a genetic-particle swarm hybrid optimization algorithm(GAPSO),aiming to enhance the disturbance resistance and control accuracy of offshore aquaculture cages under severe sea states.Based on the typical truss-type"Ri-shaped"modular cage structure and its vertical lifting mechanism,a transfer-function model of the control object is established with lifting velocity regulation as the control objective.On this basis,a fuzzy PID controller is developed,in which Gaussian membership functions,centroid defuzzification,and a fuzzy rule base are employed to realize adaptive system adjustment.Simulation results indicate that,compared with the conventional PID controller,the fuzzy PID controller reduces overshoot by 8％and shortens the response time by 24.97％.Furthermore,a genetic-particle swarm hybrid optimization algorithm is introduced to perform embedded optimization of the quantization factors and scaling factors in the fuzzy controller,thereby reducing the subjectivity of parameter tuning and improving controller robustness.Final simulation results demonstrate that the GAPSO-optimized fuzzy PID controller exhibits superior control accuracy and disturbance rejection performance under multiple disturbance conditions,with the ITAE index reduced by more than 78％compared with the conventional PID controller.