| Adaptive L_2 control of nonlinear systems using neural networks |
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| 引用本文： | Huaijing QU,Ying ZHANG,Fengtong SUN ( School of Information Science and Engineering,Shandong University,Jinan Shandong 250100,China, Singapore Institute of Manufacturing Technology,Nanyang Drive 71 638075,Singapore). Adaptive L_2 control of nonlinear systems using neural networks[J]. 控制理论与应用(英文版), 2004, 0(4) |
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| 作者姓名： | Huaijing QU Ying ZHANG Fengtong SUN ( School of Information Science and Engineering Shandong University Jinan Shandong 250100 China Singapore Institute of Manufacturing Technology Nanyang Drive 71 638075 Singapore) |
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| 作者单位： | School of Information Science and Engineering，Shandong University，Jinan Shandong 250100，China; Singapore Institute of Manufacturing Technology，Nanyang Drive 71 638075，Singapore |
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| 摘 要： | An adaptive neural network controller is developed to achieve output-tracking of a class of nonlinear systems. The global L2 stability of the closed-loop system is established. The proposed control design overcomes the limitation of the conventional adaptive neural control design where the modeling error brought by neural networks is assumed to be bounded over a compact set. Moreover,the generalized matching conditions are also relaxed in the proposed L2 control design as the gains for the external disturbances entering the system are allowed to have unknown upper bounds.
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Adaptive L_2 control of nonlinear systems using neural networks |
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| Huaijing QU,Ying ZHANG,Fengtong SUN. Adaptive L_2 control of nonlinear systems using neural networks[J]. Journal of Control Theory and Applications, 2004, 0(4) |
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| Authors: | Huaijing QU Ying ZHANG Fengtong SUN |
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| Abstract: | An adaptive neural network controller is developed to achieve output-tracking of a class of nonlinear systems. The global L2 stability of the closed-loop system is established. The proposed control design overcomes the limitation of the conventional adaptive neural control design where the modeling error brought by neural networks is assumed to be bounded over a compact set. Moreover,the generalized matching conditions are also relaxed in the proposed L2 control design as the gains for the external disturbances entering the system are allowed to have unknown upper bounds. |
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| Keywords: | Adaptive control Neural network Nonlinear systems Stability L2 controller Backstepping design |
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