基于神经网络和最大产量估算的挖泥船横移控制

针对目前绞吸挖泥船疏浚作业依靠人工手动操作无法保持较高产量的问题，研究了影响绞吸挖泥船产量的控制参数。采用神经网络预测和最大产量估算方法，得出在不同条件下挖泥船横移控制系统的最优控制参数，同时对此控制参数进行了对比仿真试验。结果表明：在一个不含边界减速的有效横移周期内，仿真产量高于实船操作产量。该方法可为绞吸挖泥船疏浚施工中横移系统的自动控制提供理论依据与技术参考，使绞吸挖泥船可以兼顾不同的控制要求和性能限制条件，在一个横移周期内稳定输出最大产量。

Lateral movement control of cutter suction dredger based on neural network and maximum output estimation

In view of the problem that the current cutter suction dredger dredging operation cannot rely on manual operation to maintain the high yield,this paper studies the control parameters affecting the yield of cutter suction dredger.By using the method of neural network prediction and maximum yield estimation,the optimal control parameters of the lateral movement control system of the dredger under different conditions are obtained.At the same time,the control parameters are compared and simulated.The simulation results show that the simulation yield is higher than that of the real ship in an effective period without boundary deceleration.The method studied in this paper can provide theoretical basis and technical reference for the automatic control of the lateral movement system in the dredging construction of cutter suction dredger,so that the cutter suction dredger can take into account different control requirements and performance constraints to stabilize the maximum output in a lateral movement cycle.