Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/97043
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Type: | Journal article |
Title: | Adaptive observer based data-driven control for nonlinear discrete-time processes |
Author: | Xu, D. Jiang, B. Shi, P. |
Citation: | IEEE Transactions on Automation Science and Engineering, 2014; 11(4):1037-1045 |
Publisher: | IEEE |
Issue Date: | 2014 |
ISSN: | 1545-5955 1558-3783 |
Statement of Responsibility: | Dezhi Xu, Bin Jiang, and Peng Shi |
Abstract: | In this paper, two adaptive observer-based strategies are proposed for control of nonlinear processes using input/output (I/O) data. In the two strategies, pseudo-partial derivative (PPD) parameter of compact form dynamic linearization and PPD vector of partial form dynamic linearization are all estimated by the adaptive observer, which are used to dynamically linearize a nonlinear system. The two proposed control algorithms are only based on the PPD parameter estimation derived online from the I/O data of the controlled system, and Lyapunov-based stability analysis is used to prove all signals of close-loop control system are bounded. A numerical example, a steam-water heat exchanger example and an experimental test show that the proposed control algorithm has a very reliable tracking ability and a satisfactory robustness to disturbances and process dynamics variations. |
Keywords: | Adaptive observer; Data-driven control; Lyapunov- based stability analysis; nonlinear discrete-time systems; pseudo-partial derivative |
Rights: | © 2013 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission |
DOI: | 10.1109/TASE.2013.2284062 |
Published version: | http://dx.doi.org/10.1109/tase.2013.2284062 |
Appears in Collections: | Aurora harvest 7 Electrical and Electronic Engineering publications |
Files in This Item:
File | Description | Size | Format | |
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hdl_97043.pdf | Accepted version | 2.74 MB | Adobe PDF | View/Open |
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