【摘要】 传统的船基收放系统中的牵引绞车一般采用速度控制方式，导致在船舶升沉作用下负载至牵引绞车之间的缆绳张力不断震荡，最终可能造成缆绳损坏，甚至断裂等问题。分别设计了基于PID、模糊PID、BP模糊神经网络PID的牵引绞车张力控制器来进行缆绳张力控制仿真。通过仿真发现，相较于其他两种控制器，所建立的BP模糊神经网络PID控制器在不规则波及不同负载下的缆绳张力控制精度最高，系统平稳、无超调，且在受到干扰时动态响应速度最快。更多还原

【Abstract】 The traction winch in the traditional ship-based retrieval system generally adopts speed control method, which leads to the constant oscillation of the cable tension between the load and the traction winch under the action of the ship lifting and sinking, which may eventually cause the cable damage or even breakage and other problems.PID,fuzzy PID and BP fuzzy neural network PID traction winch tension controllers were designed to perform cable tension control simulation.Through simulation, it is found that the established BP fuzzy neural network PID controller has the highest accuracy of cable tension control under irregular waves and different loads; the system is smooth and no overshoot, and has fastest dynamic response when subjects to disturbances compared to the other two controllers.更多还原