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作 者:CHENMou JIANGChang-sheng CHENWen-hua
机构地区:[1]CollegeofAutomationEngineering,NUAA29YudaoStreet,Nanjing,210016,P.R.China [2]DepartmentofAeronauticalandAutomotiveEngineering,LoughboroughUniversity,Loughborough,LeicestershireLE113TU,UK
出 处:《Transactions of Nanjing University of Aeronautics and Astronautics》2004年第4期304-310,共7页南京航空航天大学学报(英文版)
基 金:国家自然科学基金(60174045)资助项目。~~
摘 要:A new decentralized robust control method is discussed for a class of nonlinear interconnected largescale system with unknown bounded disturbance and unknown nonlinear function term. A decentralized control law is proposed which combines the approximation method of neural network with sliding mode control. The decentralized controller consists of an equivalent controller and an adaptive sliding mode controller. The sliding mode controller is a robust controller used to reduce the track error of the control system. The neural networks are used to approximate the unknown nonlinear functions, meanwhile the approximation errors of the neural networks are applied to the weight value updated law to improve performance of the system. Finally, an example demonstrates the availability of the decentralized control method.A new decentralized robust control method is discussed for a class of nonlinear interconnected large-scale system with unknown bounded disturbance and unknown nonlinear function term. A decentralized control law is proposed which combines the approximation method of neural network with sliding mode control. The decentralized controller consists of an equivalent controller and an adaptive sliding mode controller. The sliding mode controller is a robust controller used to reduce the track error of the control system. The neural networks are used to approximate the unknown nonlinear functions, meanwhile the approximation errors of the neural networks are applied to the weight value updated law to improve performance of the system. Finally, an example demonstrates the availability of the decentralized control method.
关 键 词:nonlinear large-scale systems neural networks sliding mode control decentralized control
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