期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：49
期号：2
出版社：Journal of Theoretical and Applied
摘要：A new method of adaptive neural network decentralized control is designed for a relevant large scale system with input saturation, it is not necessary for this method to assume that relevant items satisfy the function upper bound of high order or low order, cancel the constraint condition for known upper bound of the unknown continuous function and controlled gain of the system. It is not necessary to handle controlled gain with unknown directions by virtue of Nussbum function, only using a neural network can simultaneously approximate unknown function, unknown gains, and unknown relevant items. It can be known by using the Lyapunov theoretical analysis that the designed method can guarantee the control system to obtain overall situation stability, simulation results display that the control method is valid and feasible.
关键词：Neural Network; Input Saturation; Decentralized Control; Global Stability; Large Scale System
