DocumentCode
1386162
Title
Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems
Author
Hou, Zhongsheng ; Jin, ShangTai
Author_Institution
Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing, China
Volume
22
Issue
12
fYear
2011
Firstpage
2173
Lastpage
2188
Abstract
In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT includes compact form dynamic linearization, partial form dynamic linearization, and full form dynamic linearization. The main feature of the approach is that the controller design depends only on the measured input/output data of the controlled plant. Analysis and extensive simulations have shown that MFAC guarantees the bounded-input bounded-output stability and the tracking error convergence.
Keywords
MIMO systems; adaptive control; control system synthesis; convergence; discrete time systems; linearisation techniques; nonlinear control systems; stability; tracking; MFAC; MIMO nonlinear discrete-time system; bounded-input bounded-output stability; data-driven model-free adaptive control; dynamic linearization technique; multiple-input multiple-output nonlinear discrete-time system; pseudopartial derivative; tracking error convergence; Adaptive control; Discrete time systems; MIMO; Nonlinear dynamical systems; Compact form dynamic linearization; data-driven control; model-free adaptive control; multiple-input and multiple-output nonlinear system; partial form dynamic linearization; pseudo-partial derivative; stability; Artificial Intelligence; Data Mining; Databases, Factual; Feedback; Nonlinear Dynamics; Signal Processing, Computer-Assisted;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2011.2176141
Filename
6093751
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