Please use this identifier to cite or link to this item:
|Title:||Steady-state iterative learning control for a class of nonlinear PDE processes|
|Keywords:||Distributed parameter processes|
Steady-state iterative learning control
|Citation:||Huang, D., Xu, J.-X. (2011-09). Steady-state iterative learning control for a class of nonlinear PDE processes. Journal of Process Control 21 (8) : 1155-1163. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jprocont.2011.06.018|
|Abstract:||In this paper, a P-type steady-state iterative learning control (ILC) scheme is applied to the boundary control of a class of nonlinear processes described by partial differential equations (PDEs), which cover many important industrial processes such as heat exchangers, industrial chemical reactors, biochemical reactors, and biofilters. Under several practical properties such as physical input-output monotonicity, process stability, and repeatability, the control problem is first transformed to an output regulation problem in the spatial domain. Next, the learning convergence condition of steady-state ILC, the learning rate, as well as the robustness, are derived through rigorous analysis. The adopted ILC scheme fully utilizes the process repetition and deals with both parametric and non-parametric uncertainties. In the end, an illustrative example is presented to demonstrate the performance of the proposed ILC scheme. © 2011 Elsevier Ltd All rights reserved.|
|Source Title:||Journal of Process Control|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 12, 2018
WEB OF SCIENCETM
checked on Nov 27, 2018
checked on Dec 15, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.