Title
A matrix decomposition based adaptive control scheme for a class of MIMO non-canonical approximation systems
Abstract
This paper presents a unified study on adaptive control of multi-input multi-output (MIMO) uncertain approximation systems in non-canonical forms. For adaptive control of such systems, this paper develops a new state feedback parametrization-based adaptive control scheme, by specifying relative degrees and establishing a normal form, deriving new system reparametrizations needed for adaptive control designs, and constructing adaptive state feedback parametrized controllers for the controlled plant with different vector relative degrees, where the uncertain control gain matrices are handled using a matrix decomposition technique. The main features of such a new control framework are demonstrated by new results for non-canonical MIMO recurrent high-order neural network systems with closed-loop stability and output tracking performance analyzed. An illustrative example with simulation results is presented to show the control design procedure and desired system performance.
Year
DOI
Venue
2019
10.1016/j.automatica.2019.02.028
Automatica
Keywords
Field
DocType
Adaptive control,Approximation system,Matrix decomposition,Non-canonical form,Parametrization
Parametrization,Control theory,Matrix (mathematics),Matrix decomposition,MIMO,A-normal form,Adaptive control,Artificial neural network,Mathematics
Journal
Volume
Issue
ISSN
103
1
0005-1098
Citations 
PageRank 
References 
1
0.35
0
Authors
5
Name
Order
Citations
PageRank
Yanjun Zhang1276.28
Gang Tao21715153.52
Mou Chen3125159.31
Liyan Wen494.19
Zhengqiang Zhang541633.11