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《Journal of Northeastern University(Natural Science)》 2009-02
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Adaptive Neural Network Control of Discrete-Time Nonlinear Systems with Triangular-Form

ZHAI Lian-fei1,CHAI Tian-you1,2 (1.Key Laboratory of Integrated Automation of Process Industry,Ministry of Education,Northeastern University,Shenyang 110004,China;2.Research Center of Automation,Northeastern University,Shenyang 110004,China.)  
For a class of multi-input-multi-output(MIMO) discrete-time nonlinear systems with triangular form control inputs,an adaptive neural network control is proposed via backstepping.Due to the non-affine form of the control inputs,feedback linearization method can not be used to design control system.Therefore,implicit function theorem is firstly exploited to assert the existence of the ideal control inputs,which can compel the system outputs to track their desired trajectories,and then ideal control inputs are constructed.By using high-order neural networks to approximate the ideal control inputs,an adaptive neural network control is developed via backstepping design.All signals of the closed-loop system are proved to be semi-globally uniformly ultimately bounded under the proposed control,while the effectiveness of the proposed control is illustrated by simulations.
【Fund】: 国家高技术研究发展计划项目(2006AA04Z179);; 国家自然科学基金重点资助项目(60534010);; 国家创新研究群体科学基金资助项目(60521003);; 教育部长江学者和创新团队发展计划项目(IRT0421)
【CateGory Index】: TP273.2
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