摘要
针对压电作动器(piezoelectric actuator,PEA)的率相关迟滞非线性特性,构建了Hammerstein模型对压电作动器建模.采用径向基(radial basis function,RBF)神经网络模型表征迟滞非线性,利用自回归历遍模型(auto-regressive exogenous,ARX)表征频率的影响,并对模型参数进行了辨识.此模型可以在信号频率在1～300 Hz范围内时,较好地描述压电作动器的迟滞特性,建模相对误差为1.99%～4.08%.采用RBF神经网络前馈逆补偿控制,结合PI反馈的复合控制策略实现跟踪控制,控制误差小于2.98%,证明了控制策略的有效性.
For the rate-dependent hysteresis nonlinearity of piezoelectric actuators, a Hammerstein model is established.Using a radial-basis-function (RBF) neural network to represent the hysteresis nonlinearity, an auto-regressive exogenous (ARX) model to represent the impact of frequency, and parameter identification is also accomplished. The proposed model describes the hysteresis characteristics of frequency ranged from 1 to 300 Hz of the signals, and the relative error is 1:99%~ 4:08%. A compound control strategy with RBF neural network feedforward inverse compensation and PI feedback is utilized for position tracking control, and the relative error less than 2:98%. Validity of the control strategy is proved by experimental results.
作者
范家华
马磊
周攀
刘佳彬
周克敏
FAN Jia-hua;MA Lei;ZHOU Pan;LIU Jia-bin;ZHOU Ke-min(Institute of Systems Science and Technology, School of Electrical Engineering,Southwest Jiaotong University, Chengdu Sichuan 611756, China;School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge 70803, USA)
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2016年第7期856-862,共7页
Control Theory & Applications
基金
国家自然科学基金重点项目(61433011)资助~~
