title: H∞ output tracking control of discrete-time nonlinear systems via standard neural network models.
abstract: This brief proposes an output tracking control for a class of discrete-time nonlinear systems with disturbances. A standard neural network model is used to represent discrete-time nonlinear systems whose nonlinearity satisfies the sector conditions. H∞ control performance for the closed-loop system including the standard neural network model, the reference model, and state feedback controller is analyzed using Lyapunov-Krasovskii stability theorem and linear matrix inequality (LMI) approach. The H∞ controller, of which the parameters are obtained by solving LMIs, guarantees that the output of the closed-loop system closely tracks the output of a given reference model well, and reduces the influence of disturbances on the tracking error. Three numerical examples are provided to show the effectiveness of the proposed H∞ output tracking design approach.
authors.forename: Meiqin
authors.initials: M
authors.lastname: Liu
authors.forename: Senlin
authors.initials: S
authors.lastname: Zhang
authors.forename: Haiyang
authors.initials: H
authors.lastname: Chen
authors.forename: Weihua
authors.initials: W
authors.lastname: Sheng
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005246:Feedback; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors