Convergence Analysis of Wireless Remote Iterative Learning Control Systems with Dropout Compensation

The wireless remote iterative learning control (ILC) system with random data dropouts is considered. The data dropout is viewed as a binary switching sequence which obeys the Bernoulli distribution. In order to eliminate the effect of data dropouts on the convergence property of output error, the signal at the same time with the lost one but in the last iteration is used to compensate the data dropout at the actuator. With the dropout compensation, the convergence property of output error is analyzed by studying the element values of system transition matrix. Finally, some simulation results are given to illustrate the validity of the proposed method.

[1]  Xuhui Bu,et al.  Stability of first and high order iterative learning control with data dropouts , 2011 .

[2]  Songhwai Oh,et al.  Distributed Networked Control System with Lossy Links: State Estimation and Stabilizing Communication Control , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

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

[4]  Fang Yong,et al.  Error Estimate for Remote ILC System with Gauss Channel Noise , 2011, 2011 Fourth International Conference on Intelligent Computation Technology and Automation.

[5]  Xuhui Bu,et al.  Iterative learning control for a class of nonlinear systems with random packet losses , 2013 .

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

[7]  Yasutaka Fujimoto,et al.  A control system with high speed and real time communication links , 2006, 9th IEEE International Workshop on Advanced Motion Control, 2006..

[8]  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.

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

[10]  Guang-Hong Yang,et al.  Non-fragile state feedback H∞ control with quantized signals via LMI method , 2008, 2008 Chinese Control and Decision Conference.

[11]  Xuhui Bu,et al.  Stability of iterative learning control with data dropouts via asynchronous dynamical system , 2011, Int. J. Autom. Comput..

[12]  Ya-Jun Pan,et al.  Sampled-data iterative learning control for a class of nonlinear networked control systems , 2006, 2006 American Control Conference.

[13]  Yong Fang,et al.  Error analysis for remote nonlinear iterative learning control system with wireless channel noise , 2011 .

[14]  Yeng Chai Soh,et al.  Adaptive Kalman Filtering in Networked Systems With Random Sensor Delays, Multiple Packet Dropouts and Missing Measurements , 2010, IEEE Transactions on Signal Processing.

[15]  Lihua Xie,et al.  Optimal linear estimation for systems with multiple packet dropouts , 2008, Autom..

[16]  Tongwen Chen,et al.  Optimal ${\cal H}_{2}$ Filtering in Networked Control Systems With Multiple Packet Dropout , 2007, IEEE Transactions on Automatic Control.

[17]  Lubomír Bakule,et al.  Decentralized resilient H∞ observer-based control for a class of uncertain interconnected networked systems , 2010, Proceedings of the 2010 American Control Conference.

[18]  M. de la Sen,et al.  Decentralized stabilization of networked complex composite systems with nonlinear perturbations , 2009, 2009 IEEE International Conference on Control and Automation.

[19]  Quan Pan,et al.  Optimal Linear State Estimator With Multiple Packet Dropouts , 2010, IEEE Transactions on Automatic Control.

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

[21]  Jing Ma,et al.  Optimal Linear Estimators for Systems With Random Sensor Delays, Multiple Packet Dropouts and Uncertain Observations , 2011, IEEE Transactions on Signal Processing.

[22]  Hsiao-Hwa Chen,et al.  Distributed geographical packet forwarding in wireless sensor and actuator networks - a stochastic optimal control approach , 2012, IET Wirel. Sens. Syst..

[23]  Jun Wu,et al.  Iterative learning control for network systems with communication delay or data dropout , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.