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个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:东北大学
学位:博士
所在单位:控制科学与工程学院
学科:控制理论与控制工程. 运筹学与控制论
办公地点:创新园大厦A座722室
电子邮箱:cshao@dlut.edu.cn
基于RBF神经网络的变采样周期时延补偿策略
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发表时间:2017-01-01
发表刊物:微电子学与计算机
期号:2
页面范围:48-52,57
ISSN号:1000-7180
摘要:According to time-varying and uncertain time delays, a new variable sampling period approach is presented to mitigate the effect of time delay in this paper.Firstly, a RBF neural network with the best approximation and the global optimal performance is adopted to predict the time delay.Secondly, the time delay occurred at current sampling step is taken as the sampling period to establish the networked control system model.Then, a method in combination with optimal control and classical pole placement is used to reduce the amount of calculation and improve the system's precision and real-time performance.Finally, simulation results show that the method has a good effect on time delay compensation.
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