CAJ | 학술논문

气动加载系统具有严重非线性和参数不确定性,很难用精确的数学模型来描述,而在系统运行过程中,存在大量的输入输出数据,因此,提出一种基于数据驱动的气动加载系统在线建模方法.离线辨识阶段,基于Takagi-Sugeno模糊模型,采用减法聚类和模糊c -均值相结合的模糊聚类算法从输入输出样本数据中提取模糊规则,然后利用递推最小二乘法对后件参数进行辨识,得到离线模型;在线调参阶段,采用最小均方差算法在线修正模型线性参数,得到在线模型.基于VC++6.0软件开发平台,设计了在线建模程序,在气动变载荷摩擦磨损试验机上进行了实验研究.实验结果表明:该模型具有较高的辨识精度、较理想的泛化能力和跟踪能力,为建立气动加载系统的数学模型提供了一条新途径,同时也为气动加载系统的智能控制奠定了基础.
기동가재계통구유엄중비선성화삼수불학정성,흔난용정학적수학모형래묘술,이재계통운행과정중,존재대량적수입수출수거,인차,제출일충기우수거구동적기동가재계통재선건모방법.리선변식계단,기우Takagi-Sugeno모호모형,채용감법취류화모호c -균치상결합적모호취류산법종수입수출양본수거중제취모호규칙,연후이용체추최소이승법대후건삼수진행변식,득도리선모형;재선조삼계단,채용최소균방차산법재선수정모형선성삼수,득도재선모형.기우VC++6.0연건개발평태,설계료재선건모정서,재기동변재하마찰마손시험궤상진행료실험연구.실험결과표명:해모형구유교고적변식정도、교이상적범화능력화근종능력,위건립기동가재계통적수학모형제공료일조신도경,동시야위기동가재계통적지능공제전정료기출.
@@@@Pneumatic loading system has the characteristics of serious nonlinearity and parameter uncertainty,it is difficult to de-scribe the system by accurate mathematical model. There are a large number of input/ output data while the system is running. So an online modeling method based on data-driven was proposed for the pneumatic loading system. On the offline stage,subtractive cluste-ring and fuzzy c - means clustering (FCM)were combined to extract fuzzy rules from the input and output data,and then recursive least squares method was used to identify the consequent parameters. On the online stage,least mean square algorithm was adopted to adjust the parameters of the model. Based on VC++ 6. 0 software development platform,online fuzzy modeling program was designed and tested on a pneumatic variable-loading friction and wear tester. The results show that the model has high identification accuracy, satisfactory generalization ability and tracking ability. It provides a new way to establish the mathematical model for pneumatic loading system. Furthermore,it lays foundation for the design of intelligent control algorithms for pneumatic loading system.