Convergence Analysis of Iterative Learning Control Systems Over Networks With Successive Input Data Compensation in Iteration Domain

This paper analyzes the convergence of iterative learning control for a class of discrete-time systems over networks with successive input data compensation. Specifically, the successively dropped input data in current iterations are compensated by the one actuator received correctly with the same time instant label in the latest iteration. Through analyzing the variation of elements in the transition matrices of the input errors at the controller side, the convergence of output errors is addressed. The analysis shows the selection range of learning gain is determined by the maximum number of input data dropped successively. Moreover, the convergence of system with successive input data compensation is guaranteed by trading the convergence speed, and the more input data are successively compensated in iteration domain, the more convergence speed of the system is reduced. Finally, numerical experiments are given to corroborate the theoretical analysis.

[1]  Samer S. Saab.  Optimal selection of the forgetting matrix into an iterative learning control algorithm , 2005, IEEE Transactions on Automatic Control.

[2]  Jian Liu,et al.  Networked Iterative Learning Control Design for Nonlinear Systems with Stochastic Output Packet Dropouts , 2018 .

[3]  Kevin L. Moore,et al.  Discrete-time Intermittent Iterative Learning Controller with Independent Data Dropouts , 2008 .

[4]  Tao Wang,et al.  Method to improve convergence performance of iterative learning control systems over wireless networks in presence of channel noise , 2014 .

[5]  Jun Wu,et al.  Iterative Learning Control for Remote Control Systems with Communication Delay and Data Dropout , 2012 .

[6]  Kevin L. Moore,et al.  Stability of discrete-time iterative learning control with random data dropouts and delayed controlled signals in networked control systems , 2008, 2008 10th International Conference on Control, Automation, Robotics and Vision.

[7]  Dong Shen,et al.  A Novel Markov Chain Based ILC Analysis for Linear Stochastic Systems Under General Data Dropouts Environments , 2017, IEEE Transactions on Automatic Control.

[8]  Dong Shen,et al.  Two updating schemes of iterative learning control for networked control systems with random data dropouts , 2017, Inf. Sci..

[9]  Dong Shen,et al.  ILC for networked nonlinear systems with unknown control direction through random Lossy channel , 2015, Syst. Control. Lett..

[10]  Dong Shen,et al.  Iterative learning control with incomplete information: a survey , 2018, IEEE/CAA Journal of Automatica Sinica.

[11]  Jian Liu,et al.  Networked iterative learning control design for discrete-time systems with stochastic communication delay in input and output channels , 2017, Int. J. Syst. Sci..

[12]  Dong Shen,et al.  Iterative learning control for networked stochastic systems with random packet losses , 2014, Int. J. Control.

[13]  Dinh Hoa Nguyen,et al.  Robust Iterative Learning Control for linear systems with iteration-varying parametric uncertainties , 2009, 2009 7th Asian Control Conference.

[14]  Kevin L. Moore,et al.  Stability analysis of discrete-time iterative learning control systems with interval uncertainty , 2007, Autom..

[15]  Kwang-Hyun Park,et al.  A generalized iterative learning controller against initial state error , 2000 .

[16]  A.G. Alleyne,et al.  A survey of iterative learning control , 2006, IEEE Control Systems.

[17]  Suguru Arimoto,et al.  Bettering operation of Robots by learning , 1984, J. Field Robotics.

[18]  Xuhui Bu,et al.  H∞ iterative learning controller design for a class of discrete-time systems with data dropouts , 2014, Int. J. Syst. Sci..

[19]  Dong Shen,et al.  A framework of iterative learning control under random data dropouts: Mean square and almost sure convergence , 2017 .

[20]  Bu Xuhui,et al.  An iterative learning control design approach for networked control systems with data dropouts , 2016 .

[21]  Tong Duy Son,et al.  Robust Monotonic Convergent Iterative Learning Control , 2016, IEEE Transactions on Automatic Control.

[22]  Bu Xuhui,et al.  Robust iterative learning control design for linear systems with time-varying delays and packet dropouts , 2017, Advances in Difference Equations.

[23]  Jian Liu,et al.  Networked iterative learning control approach for nonlinear systems with random communication delay , 2016, Int. J. Syst. Sci..

[24]  Bu Xuhui,et al.  Iterative learning control for discrete-time systems with quantised measurements , 2015 .

[25]  Ya-Jun Pan,et al.  Effects of network communications on a class of learning controlled non-linear systems , 2009, Int. J. Syst. Sci..

[26]  YangQuan Chen,et al.  Intermittent iterative learning control , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[27]  Tao Wang,et al.  Convergence Analysis of Wireless Remote Iterative Learning Control Systems with Channel Noise: Convergence Analysis of Wireless Remote ILC Systems with Channel Noise , 2015 .

[28]  Yong Fang,et al.  Convergence Analysis of Wireless Remote Iterative Learning Control Systems with Dropout Compensation , 2013 .

[29]  Frank L. Lewis,et al.  Recent Developments in Networked Control and Estimation , 2014 .