Dynamic Modeling and Boundary Control of Flexible Axially Moving System

Professor Yu Liu received his PhD from the School of Automation Science and Engineering, South China University of Technology, Guangzhou, China, in 2009. He was a Visiting Student with the Department of Mechanical Engineering, Concordia University, Montreal, QC, Canada, from 2008 to 2009, and a Visiting Scholar with the Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA, from 2017 to 2018. He is currently a Full Professor with the School of Automation Science and Engineering, South China University of Technology, Guangzhou, China, and with the R&D Center of Precision Electronic Manufacturing Technology, Guangzhou Institute of Modern Industrial Technology, Guangzhou, China. He is serving as the Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Computational Social Systems and International Journal of Space-Based and Situated Computing. His current research interests include distributed parameter systems, intelligent control system, robotics, intelligent perception and decision making and machine vision.

• Introduction.- Mathematical Preliminaries.- PDE Modeling for Flexible Manipulator.- Boundary Control Using Singular Perturbation Approach.- Robust boundary control of an axially moving system.- Adaptive boundary control of an axially moving system with high acceleration/deceleration.- Adaptive boundary control of an axially moving belt system with high acceleration/deceleration.- Boundary control of an axially moving accelerated/decelerated.-  Stabilization of anaxially moving accelerated/decelerated system.- Adaptive output feedback boundary control.- Vibration control and boundary tension constraint of an axially moving string system.- Boundary Control for an Axially Moving System With Input Restriction Based on Disturbance Observers.- Adaptive Neural Network Vibration Control for an Output-Tension-Constrained Axially Moving Belt System With Input Nonlinearity.- Conclusion.