Data-driven control for relative degree systems via iterative learning

IEEE Transactions on Neural Networks

Volumn 22, Issue 12 PART 2, 2011, Pages 2213-2225

  Meng, Deyuan ^a   Jia, Yingmin ^a   Du, Junping ^b   Yu, Fashan ^c  

^a BEIHANG UNIVERSITY   (China)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^c HENAN POLYTECHNIC UNIVERSITY   (China)

Author keywords

Data driven control; higher order relative degree; iterative learning control; linear matrix inequality; monotonic convergence

Indexed keywords

ANALYSIS APPROACH; CONTINUOUS TIME; CONVERGENCE CONDITIONS; DATA-DRIVEN CONTROL; DATA-DRIVEN METHODS; DESIGN APPROACHES; DISCRETE-TIME; HIGHER ORDER; INPUT/OUTPUT DATUM; ITERATIVE LEARNING; ITERATIVE LEARNING CONTROL; MONOTONIC CONVERGENCE; OFFLINE; RELATIVE DEGREES; SYSTEM FRAMEWORK;

ASYMPTOTIC STABILITY; CONTINUOUS TIME SYSTEMS; CONTROL SYSTEM STABILITY; LEARNING ALGORITHMS; LINEAR MATRIX INEQUALITIES; ONLINE SYSTEMS;

TWO TERM CONTROL SYSTEMS;

ARTICLE; ARTIFICIAL INTELLIGENCE; DATA MINING; FACTUAL DATABASE; FEEDBACK SYSTEM; METHODOLOGY; THEORETICAL MODEL;

ARTIFICIAL INTELLIGENCE; DATA MINING; DATABASES, FACTUAL; FEEDBACK; MODELS, THEORETICAL;

EID: 83655184652     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2011.2174378     Document Type: Article

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