基于改进粒子群算法的柴油机振动控制技术研究  

Study on Vibration Control Strategy of Marine Diesel Engine based on Improved PSO Algorithm

作　　者：胡甫才[1] 薛厚强 魏志威 徐阳 高硕 Hu Fucai;Xue Houqiang;Wei Zhiwei;Xu Yang;Gao Shuo(School of Energy and Power Engineering,Wuhan University of Technology(Wuhan,Hubei,430063,China))

机构地区：[1]武汉理工大学能源与动力工程学院,湖北武汉430063

出　　处：《小型内燃机与车辆技术》2018年第6期56-61,共6页Small Internal Combustion Engine and Vehicle Technique

摘　　要：针对柴油机传统的PID振动控制器存在时滞性、人工整定参数困难,难以达到最佳减振效果这一问题,采用基于改进粒子群算法的控制器参数整定方法。在分析了振动控制系统之后,将控制器参数作为研究对象并引入粒子群算法对控制器的参数进行迭代寻优,在此基础上采用基于动态加速常数的粒子群算法,来提高粒子多样性同时加快粒子搜索目标的速度。仿真结果表明,对比传统人工及传统粒子群算法整定参数的方法,改进粒子群算法适应度更好,能够解决振动控制系统人工参数整定困难的问题,且优化后的控制器具有更好的控制效果。To solve the problem that the traditional PID vibration controller of diesel engine has the problems of time delay and manual setting parameters,it is difficult to achieve the optimal damping effect,and a new controller parameter tuning method based on improved particle swarm optimization algorithm is used.After analyzing the vibration control system,taking the controller parameters as the research object and introducing the particle swarm optimization algorithm to iterative optimization of the controller parameters,a particle swarm optimization algorithm based on dynamic acceleration constant is used to improve the particle diversity and speed up the particle's searching target.The simulation results show that compared with traditional artificial and traditional PSO algorithm,the improved particle swarm optimization(PSO)algorithm has better adaptability and can solve the difficulty of manual parameter setting in vibration control system,and the optimized controller has better control effect.

关 键 词：柴油机 粒子群算法 动态加速 振动控制 

分 类 号：TK421.6[动力工程及工程热物理—动力机械及工程]