摘要
The stabilization problem is considered in this study for a nonlinear system. It is shown that the stability analysis of nonlinear systems can be reduced into linear matrix inequality (LMI) problems. First, the neural-network (NN) model is employed to approximate a nonlinear system via the back propagation algorithm. Then, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. In terms of Lyapunov’s direct method, a sufficient condition is provided to guarantee the stability of nonlinear systems. Based on this criterion, a model based fuzzy controller is then designed to stabilize the nonlinear system and the H control performance is achieved at the same time. Finally, two examples with numerical simulations are given to illustrate the control methodology.
原文 | ???core.languages.en_GB??? |
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頁(從 - 到) | 145-152 |
頁數 | 8 |
期刊 | International Journal of Computational Methods in Engineering Science and Mechanics |
卷 | 6 |
發行號 | 3 |
DOIs | |
出版狀態 | 已出版 - 2005 |