东南大学学报（自然科学版）2017，Vol.47Issue(6)：1086-1093,8.DOI:10.3969/j.issn.1001-0505.2017.06.002
基于最优结构多维泰勒网的含噪声非线性时变系统辨识
Identification of nonlinear time-varying system with noise based on multi-dimensional Taylor network with optimal structure
摘要
Abstract
Aiming at the modeling difficulties of the nonlinear time-varying system with noise disturbance,a multi-dimensional Taylor network (MTN) model with optimal structure and optimum generalization ability is established to implement the identification of the system.Firstly,to rapidly reflect the input-output changes of the system,the link weight coefficients of MTN are taken as the time-varying parameters,and then the recursive least-squares algorithm with a variable forgetting factor is adopted to train the system and the stability of the identification scheme is addressed.Secondly,to avoid the dimension curse and meet the real-time requirements,an improved pruning algorithm is developed to choose the effective regression items of MTN,which provides the network with the simplest structure and optimum generalization ability.Finally,an example is given to illustrate the application of the MTN with minimum structure in the identification of a nonlinear time-varying system with noise disturbance,and the experimental results demonstrate the effectiveness of the proposed method.关键词
辨识/非线性时变系统/多维泰勒网/噪声干扰/剪枝算法Key words
identification/nonlinear time-varying system/multi-dimensional Taylor network/noise disturbance/pruning algorithm分类
通用工业技术引用本文复制引用
张超,严洪森..基于最优结构多维泰勒网的含噪声非线性时变系统辨识[J].东南大学学报（自然科学版）,2017,47(6):1086-1093,8.基金项目
国家自然科学基金资助项目(61673112,60934008)、中央高校基本科研业务费专项资金资助项目(2242017K10003,2242014K10031)、江苏高校优势学科建设工程资助项目. （61673112,60934008）
