船舶柴油机转速模糊神经网络PID智能控制  

Intelligent speed control of marine diesel engine based on fuzzy neural network PID

作　　者：徐红明[1] 吴震[1,2] 周波 周微 XU Hong-ming;WU Zhen;ZHOU Bo;ZHOU Wei(School of Maritime,Zhejiang Institute of Communications,Hangzhou 311112,China;School of Mechanical Engineering and Automation,Zhejiang SCI-TECH University,Hangzhou 311118,China;College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China)

机构地区：[1]浙江交通职业技术学院海运学院,浙江杭州311112 [2]浙江理工大学机械与自动控制学院,浙江杭州310018 [3]浙江工业大学信息工程学院,浙江杭州310023

出　　处：《舰船科学技术》2022年第21期101-105,共5页Ship Science and Technology

基　　金：浙江省高校访问工程师“校企合作项目”(FG2017013);浙江省高等教育“十三五”教学改革研究项目(jg20190699)。

摘　　要：为了提高常规PID控制器在非线性、时变不确定性系统中的控制性能,提出一种模糊神经网络PID控制算法,利用模糊控制良好的非线性控制优势,以及神经网络超强的自学习、自适应特性,实现对PID参数的实时在线整定,并建立船舶柴油机转速模糊神经网络PID控制系统数学模型,利用Matlab/Simulink进行仿真。仿真结果表明,模糊神经网络PID控制超调量少、精度高、调节时间短,具有更好的动静态特性和抗干扰特性,系统鲁棒性有了很大提升,能很好地满足船舶柴油机转速控制系统的要求。In order to improve the control performance of nonlinear and time-varying uncertain system,a fuzzy neural network PID control algorithm is proposed,which realizes the real-time online tuning of PID parameters by taking advantage of the nonlinear control advantages of fuzzy control as well as the super self-learning and self-adaptive characteristics of neural network.The mathematical model of fuzzy neural network PID control for marine diesel engine speed is established,the simulation results show that the fuzzy neural network PID control has less overshoot, high precision, short adjustment time, better dynamic and static characteristics and anti-interference characteristics, and the robustness of the system has been greatly improved. It can well meet the requirements of speed control system of Marine diesel engine.

关 键 词：船舶柴油机 模糊神经网络 转速控制 MATLAB仿真 

分 类 号：U664.121[交通运输工程—船舶及航道工程] TK427[交通运输工程—船舶与海洋工程]