Tracking control is a very challenging problem in the networked control system(NCS), especially for the process with blurred mechanism and where only input-output data are available. This paper has proposed a data-based design approach for the networked tracking control system(NTCS). The method utilizes the input-output data of the controlled process to establish a predictive model with the help of fuzzy cluster modelling(FCM)technology. Then, the deduced error and error change in the future are treated as inputs of a fuzzy sliding mode controller(FSMC) to obtain a string of future control actions. These candidate control actions in the controller side are delivered to the plant side. Thus, the network induced time delays are compensated by selecting appropriate control action. Simulation outputs prove the validity of the proposed method.
IEEE/CAA Journal of Automatica Sinica
supported by the National Natural Science Foundation of China(51205025,51775048,61602041)
the Science and Technology Program of Beijing Municipal Education Commission(KM201611417009,KM201811417001)
the Premium Funding Project(BPHR2017CZ08) for Academic Human Resources Development in Beijing Union University(BUU)
the Beijing Natural Science Foundation- Beijing Municipal Education Commission Joint Fund(KZ201811417048)
the Project of 2018-2019 Basic Research Fund of BUU
the Beijing Advanced Innovation Center for Intelligent Robots and Systems Open Fund(2018IRS17)
the 2016 Beijing High Level Personnel Cross Training Program “Practical Training Plan”
the Project of Beijing Municipal Natural Science Foundation(4142018)
the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions(CIT&TCD20150314).
Corresponding author:Shiwen Tong received the B.E.degree in chemical engineering from the University of Petroleum (East China),Shandong,China,in 1999,the M.E.degree in control theory and control engineering from the University of Petroleum (Beijing),Beijing,China,in 2003,and the Ph.D.degree from the Institute of Automation,Chinese Academy of Sciences,Beijing,China,in 2008.He was an operator with Liaohe Oil Field Petrochemical Refinery from 1999-2002,an Engineer with Beijing Anwenyou Science and Technology Company,Ltd.from 2003-2005,and an instrument Senior Engineer with China Tianchen Engineering Corporation (TCC) from 2008-2012.He is currently a Professor with the College of Robotics,Beijing Union University,Beijing,China.His research interests include the intelligent control,networked control,PEM fuel cell,and their industrial applications.e-mail:email@example.com;Dianwei Qian received the B.E.degree from Hohai University,Nanjing,China,in 2003.In 2005 and 2008,He received the M.E.degree from Northeastern University,Shenyang,China,and the Ph.D.degree from the Institute of Automation,Chinese Academy of Sciences,Beijing,China,respectively.Currently,he is an Associate Professor at the School of Control and Computer Engineering,North China Electric Power University,Beijing,China.His research interests include theories and applications of intelligent control,nonlinear control,etc.e-mail:dianwei.qian @ncepu.edu.cn;Xiaoyu Yan received the B.E.degree in logistics engineering from Beijing Union University,Beijing,China,in 2016,and received the M.E.degree in vocational and technical education from Beijing Union University,China,in 2018.She is currently a primary school English Teacher at Aidi School in Tianjin,China.Her research interests include education,networked control and robotics.e-mail:firstname.lastname@example.org;Jianjun Fang received the bachelor degree in mechanical engineering from Central China Agricultural University in 1993 and Ph.D.degree in Mechanical Engineering from China Agricultural University.From 1998 to