Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75470
Title: Design and analysis of FTZNN applied to the real-time solution of a nonstationary lyapunov equation and tracking control of a wheeled mobile manipulator
Authors: Xiao, L
Liao, B
Li, S 
Zhang, Z
Ding, L
Jin, L
Keywords: Finite-time convergence
Nonstationary Lyapunov equation
Tracking control
Upper bound
Wheeled mobile manipulator
Zhang neural network (ZNN)
Issue Date: 2018
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on industrial informatics, 2018, v. 14, no. 1, 7953678, p. 98-105 How to cite?
Journal: IEEE transactions on industrial informatics 
Abstract: The Lyapunov equation is widely employed in the engineering field to analyze stability of dynamic systems. In this paper, based on a new evolution formula, a novel finite-time recurrent neural network (termed finite-time Zhang neural network, FTZNN) is proposed and studied for solving a nonstationary Lyapunov equation. In comparison with the original Zhang neural network (ZNN) model for a nonstationary Lyapunov equation, the convergence performance has a remarkable improvement for the proposed FTZNN model and can be accelerated to finite time. Besides, by solving the differential inequality, the time upper bound of the FTZNN model is computed theoretically and analytically. Simulations are conducted and compared to validate the superiority of the FTZNN model to the original ZNN model for solving the nonstationary Lyapunov equation. At last, the FTZNN model is successfully applied to online tracking control of a wheeled mobile manipulator.
URI: http://hdl.handle.net/10397/75470
ISSN: 1551-3203
EISSN: 1941-0050
DOI: 10.1109/TII.2017.2717020
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