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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
Statement of
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
Appears in Collections:Aurora harvest 7
Electrical and Electronic Engineering publications

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