A Robust Controller Design Method Based on Parameter Variation Rate of RBF-ARX Model
A Robust Controller Design Method Based on Parameter Variation Rate of RBF-ARX Model
复制标题
基于RBF-ARX模型参数变化率的鲁棒控制器设计方法
DOI：
10.1109/access.2019.2951390
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发表时间：
2019
期刊：
影响因子：
3.9
通讯作者：
Zeng Xiaoyong
中科院分区：
文献类型：
--
作者：
Zhou Feng;Peng Hui;Zhang Ganglin;Zeng Xiaoyong
RBF- arx模型作为指数自回归模型和径向基函数（RBF）网络的扩展，在非线性系统建模和控制中得到了广泛的应用。考虑到以往方法仅使用RBF-ARX模型参数的上下限来构建系统的多面体状态空间模型的保守性，本文还利用模型的参数变化率信息来压缩系统状态空间模型中系数矩阵的变化范围。然后，设计了一种不使用系统稳态信息的鲁棒预测控制（RPC）输出跟踪策略。构造系统多面体状态空间模型的方法利用了RBF-ARX模型本身是一种特殊的准lpv模型，不需要假设系统模型中时变参数和/或参数变化率是已知或可测量的。在连续搅拌槽式反应器（CSTR）过程中验证了该控制策略的有效性。
As an extension of the exponential autoregressive model and radial basis function (RBF) network, the RBF-ARX model has been widely used in nonlinear system modeling and control. Considering conservativeness of the previous method, which only uses the upper and lower limits of the RBF-ARX model parameters to construct a system’s polytopic state space model, in this paper, the model’s parameter variation rate information is also utilized to compress variation range of the coefficient matrices in the system’s state space model. And then, a robust predictive control (RPC) strategy for output tracking without using system’s steady state information is designed. The method of constructing the system’s polytopic state space model takes advantage of the fact that the RBF-ARX model itself is a special quasi-LPV model, and there is no need to assume the time varying parameters and/or the variation rate of the parameters in the system model are known or measurable. The effectiveness of the proposed control strategy is verified on a continuous stirred tank reactor (CSTR) process.