The structured nonlinear parameters optimization method (SNPOM) is generally used to optimize model parameters, but this method is very complicated and hard to be mastered by engineers. However, genetic algorithm (GA) is simple and widely used. So the thought of GA optimizing RBF‐ARX is ...
基于RBF-ARX模型的非线性系统建模和预测控制在磁悬浮系统中的应用.doc,分类号 密级 U D C 编号 CENTRAL SOUTH UNIVERSITY 硕士学位论文 MS THESIS: The RBF-ARX Model-based Nonlinear System Modeling and Predictive Control to Magnetic Levitation System Specialty: Co
pendulum,Modeling,RBF-ARXmodel, PredictivecontrolbasedonlocalRBF.ARXmodel Ill 原创性声明 本人声明,所呈交的学位论文是本人在导师指导下进行的研究 工作及取得的研究成果。尽我所知,除了论文中特别加以标注和致谢 的地方外,论文中不包含其他人已经发表或撰写过的研究成果,也不 ...
The combination models are constructed on the basis of a matrix polynomial multi-input multi-output (MIMO) RBF-ARX model identified offline for representing the underlying nonlinear system. A min–max robust MPC strategy is designed to achieve the systems’ output-tracking control based on the ...
为了充分描述磁悬浮球系统具有非线性,开环不稳定性及响应快速性等特性,建立一个带线性函数权重的RBF-ARX(linear functional weight RBF networks-based ARX model,LFW... 覃业梅,彭辉,阮文杰 - 《中南大学学报(自然科学版)》 被引量: 3发表: 2016年 基于RBF-ARX模型的双体无人船航向控制 为了提高双体船的机动性...
现今,锂离子电池剩余容量估计方法主要可以分为两类:模型构建法(Model-based Method)与数据驱动法(Data-driven Method)。其中,模型构建法的主要对象为等效电路模型(Equivalent Circuit Model)。 如将等效电路模型与深度学习、迁移学习相结合,提出一种高效的电池容量估计方法。还有通过等效电路模型来表示电池动态特性,提出一...
Firstly, from the RBF-ARX model that is identified using input/output data of the system, the two local linearization state-space models that consider the bounded disturbance and a polytopic uncertain LPV state-space model are built to approximate the present and future system...
RBF-ARX modelCycle forecastingStructured nonlinear parameter optimization methodShort-term load forecasting plays a vital role for the power system's safe operation and production arrangements. This paper regards electric load forecasting as a nonlinear time series prediction problem, and establishes the ...
First, the nonlinear system is identified off-line by a RBF-ARX model possessing linear ARX model structure and state-dependent Gaussian RBF neural network type coefficients. On the basis of the RBF-ARX model, a combination of a local linearization model and a polytopic uncertain linear parameter...
First, the nonlinear system is identified off-line by a RBF-ARX model possessing linear ARX model structure and state-dependent Gaussian RBF neural network type coefficients. On the basis of the RBF-ARX model, a combination of a local linearization model and a polytopic uncertain linear parameter...