Iterative Learning Control of a Multiagent System under Random Perturbations

A multiagent system in which each of the agents is described by a linear discrete-time model with random perturbations (external random disturbances affecting the plant and measurement noises) is considered. Networked modifications of iterative learning control laws based on minimizing the deviations from a reference model and also based on the theory of stochastic stability of repetitive processes using the divergent method of vector Lyapunov functions are proposed. These modifications are compared with each other by an illustrative example of iterative learning control for a group of gantry robots.

[1]  A.G. Alleyne,et al.  Iterative Learning Control for robotic deposition using machine vision , 2008, 2008 American Control Conference.

[2]  Francis J. Doyle,et al.  Survey on iterative learning control, repetitive control, and run-to-run control , 2009 .

[3]  Robert G. Landers,et al.  Repetitive Process Control of Additive Manufacturing With Application to Laser Metal Deposition , 2019, IEEE Transactions on Control Systems Technology.

[4]  Krzysztof Galkowski,et al.  Experimentally supported 2D systems based iterative learning control law design for error convergence and performance , 2010 .

[5]  Pavel V. Pakshin,et al.  Iterative Learning Control Design for Multiagent Systems Based on 2D Models , 2018, Autom. Remote. Control..

[6]  K. Moore,et al.  Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems , 2010 .

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

[8]  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..

[9]  Samer S. Saab,et al.  A discrete-time stochastic learning control algorithm , 2001, IEEE Trans. Autom. Control..

[10]  S. Saab.  A stochastic iterative learning control algorithm with application to an induction motor , 2004 .

[11]  Kevin L. Moore,et al.  Iterative Learning Control: Brief Survey and Categorization , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[12]  Qing Liu,et al.  An iteration-domain filter for controlling transient growth in Iterative Learning Control , 2010, Proceedings of the 2010 American Control Conference.

[13]  Eric Rogers,et al.  Iterative Learning Control Design for Discrete Stochastic Linear Systems , 2019, 2019 18th European Control Conference (ECC).

[14]  Samer S. Saab.  Optimality of first-order ILC among higher order ILC , 2006, IEEE Transactions on Automatic Control.

[15]  Dong Shen,et al.  Survey on stochastic iterative learning control , 2014 .

[16]  Frank Doyle.  Open Access Publishing [Publication Activities] , 2012 .

[17]  E. Rogers,et al.  Iterative Learning Control in Health Care: Electrical Stimulation and Robotic-Assisted Upper-Limb Stroke Rehabilitation , 2012, IEEE Control Systems.

[18]  S. Saab.  Stochastic P-type/D-type iterative learning control algorithms , 2003 .

[19]  Se-Kyu Oh,et al.  Stochastic iterative learning control for discrete linear time-invariant system with batch-varying reference trajectories , 2015 .

[20]  Jian-Xin Xu,et al.  An iterative learning control approach for synchronization of multi-agent systems under iteration-varying graph , 2013, 52nd IEEE Conference on Decision and Control.

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

[22]  Yang Liu,et al.  An iterative learning approach to formation control of multi-agent systems , 2012, Syst. Control. Lett..

[23]  Junping Du,et al.  On iterative learning algorithms for the formation control of nonlinear multi-agent systems , 2014, Autom..

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

[25]  Peter B. Goldsmith.  Author's reply to "Comments on 'On the Equivalence of Causal LTI Iterative Learning Control and Feedback Control"' , 2004, Autom..

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

[27]  F. Miyazaki,et al.  Bettering operation of dynamic systems by learning: A new control theory for servomechanism or mechatronics systems , 1984, The 23rd IEEE Conference on Decision and Control.

[28]  John J. Craig,et al.  Adaptive control of manipulators through repeated trials , 1984 .

[29]  Eric Rogers,et al.  Comments on 'On the equivalence of causal LTI iterative learning control and feedback control' , 2004, Autom..

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

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

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

[33]  Krzysztof Galkowski,et al.  Control Systems Theory and Applications for Linear Repetitive Processes - Recent Progress and Open Research Questions , 2007 .

[34]  Jian-Xin Xu,et al.  Iterative learning control for multi-agent systems consensus tracking , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[35]  Dong Shen,et al.  A Technical Overview of Recent Progresses on Stochastic Iterative Learning Control , 2018, Unmanned Syst..

[36]  Peter B. Goldsmith.  On the equivalence of causal LTI iterative learning control and feedback control , 2002, Autom..

[37]  YangQuan Chen,et al.  Iterative learning control for multi-agent formation , 2009, 2009 ICCAS-SICE.

[38]  Magnus Egerstedt,et al.  Graph Theoretic Methods in Multiagent Networks , 2010, Princeton Series in Applied Mathematics.