检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:顾文斌[1,2] 杨生胜 王贤良 苑明海 GU Wen-bin;YANG Sheng-sheng;WANG Xian-liang;YUAN Ming-hai(School of Mechanical and Electrical Engineering,Hohai University,Changzhou 213022,China;Institute of Ocean and Offshore Engineering,Nantong Hohai University,Nantong 226004,China)
机构地区:[1]河海大学机电工程学院,江苏常州213022 [2]南通河海大学海洋与近海工程研究院,江苏南通226004
出 处:《计算机技术与发展》2022年第8期15-19,25,共6页Computer Technology and Development
基 金:国家自然科学基金资助项目(51875171);江苏省自然科学基金面上项目(SBK2020022560);南通市基础科学研究项目(JC2021197)。
摘 要:针对无刷直流电机在传统PID控制方式下,存在抗干扰能力差、响应速度慢以及控制精度低等问题,提出一种基于模糊径向基函数(RBF)神经网络的无刷直流电机PID控制策略。首先,利用模糊控制不需要精确数学模型的优势,能够克服传统PID对数学模型的依赖性,而模糊控制规则的制定主要取决于经验,因此,将RBF神经网络与模糊控制相结合,可以提高其自学习、自适应能力。此外,利用改进蚁群算法对模糊神经网络的参数进行初始化,避免了在传统聚类方法下陷入局部最优的困境,同时提高了模糊神经网络的收敛速度,然后将列文伯格-马夸尔特算法融入模糊神经网络,以确定神经网络的权值,并提高神经网络的训练速度。最后,在Simulink中通过仿真与其他控制策略进行对比。仿真结果表明,模糊RBF神经网络PID控制策略相较于其他控制策略,在无刷直流电机控制系统中具有更优异的控制性能。In order to solve the problems of poor anti-interference ability,slow response speed and low control precision under the traditional PID control mode of brushless DC motor,a PID control strategy of brushless DC motor based on fuzzy radial basis function(RBF)neural network is proposed.First of all,the use of fuzzy control does not need the advantage of precise mathematical model,can overcome the dependency of traditional PID on mathematical model,and the formulation of fuzzy control rules mainly depends on experience.Therefore,the combination of RBF neural network and fuzzy control can improve its self-learning,self-adaptive ability.In addition,the improved ant colony algorithm is used to initialize the parameters of the fuzzy neural network,which avoids the dilemma of falling into local optimization under the traditional clustering method and improves the convergence speed of the fuzzy neural network.Then,the Levenberg-Marquardt algorithm is integrated into the fuzzy neural network to determine the weight of the neural network and improve the training speed of the neural network.Finally,the simulation is compared with other control strategies in Simulink,which shows that the fuzzy RBF neural network PID control strategy has better control performance than other control strategies in the brushless DC motor control system.
关 键 词:无刷直流电机 模糊径向基函数 改进蚁群算法 LM算法 PID控制
分 类 号:TP273[自动化与计算机技术—检测技术与自动化装置]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.7