A bias-corrected estimator for nonlinear systems with output-error type model structures

Automatica ◽  
2014 ◽  
Vol 50 (9) ◽  
pp. 2373-2380 ◽  
Author(s):  
Dario Piga ◽  
Roland Tóth
Keyword(s):  
Nonlinear Systems ◽  
Type Model ◽  
Error Type ◽  
Output Error ◽  
Model Structures

Asymptotic variance expressions for output error model structures

1999 ◽  
Vol 32 (2) ◽  
pp. 4135-4140 ◽  
Author(s):  
Brett Ninness ◽  
Håkan Hjalmarsson ◽  
Fredrik Gustafsson
Keyword(s):  
Asymptotic Variance ◽  
Error Model ◽  
Output Error ◽  
Model Structures

scholarly journals MODELING AND IDENTIFICATION OF NONLINEAR SYSTEMS USING SISO LEM-HAMMERSTEIN AND LEM-WIENER MODEL STRUCTURES

2006 ◽  
Vol 39 (2) ◽  
pp. 1101-1106
Author(s):  
P. Bolognese Fernandes ◽  
D. Schlipf ◽  
J.O. Trierweiler
Keyword(s):  
Nonlinear Systems ◽  
Wiener Model ◽  
Model Structures

scholarly journals Distributed Wireless NetworkedH∞Control for a Class of Lurie-Type Nonlinear Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
Wen Ren ◽  
Bugong Xu
Keyword(s):  
Nonlinear Systems ◽  
Fading Channels ◽  
Neural Control ◽  
Geographical Area ◽  
Disturbance Attenuation ◽  
Type Model ◽  
New Approach ◽  
Attenuation Index ◽  
Communication Links ◽  
Distributed Control Problem

A new approach to solving the distributed control problem for a class of discrete-time nonlinear systems via a wireless neural control network (WNCN) is presented in this paper. A unified Lurie-type model termed delayed standard neural network model (DSNNM) is used to describe these nonlinear systems. We assume that all neuron nodes in WNCN which have limited energy, storage space, and computing ability can be regarded as a subcontroller, then the whole WNCN is characterized by a mesh-like structure with partially connected neurons distributed over a wide geographical area, which can be considered as a fully distributed nonlinear output feedback dynamic controller. The unreliable wireless communication links within WNCN are modeled by fading channels. Based on the Lyapunov functional and the S-procedure, the WNCN is solved and configured for the DSNNM to absolutely stabilize the whole closed-loop system in the sense of mean square with aH∞disturbance attenuation index using LMI approach. A numerical example shows the effectiveness of the proposed design approaches.

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