NN-Based Adaptive Output Feedback Stabilization via Passivation of MIMO Uncertain System

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An NN-based output feedback stabilization problem is studied via passivation of a class of multi-input multi-output nonlinear systems with unknown nonlinear input matrix and unknown parameters. Neural networks are used to identify unknown nonlinearities, and the update laws of weight parameters are proposed. The design methods of the adaptive passive controllers for this class of systems are discussed in the paper. The corresponding adaptive passive controllers and parametric adaptive laws are designed and presented respectively. It is proved that the closed-loop system composed of the original system and the designed controller is stable by the Lyapunov method, and the controller designed can render the closed system adaptive passive. Finally, a simulation example is given to prove the effectiveness and feasibility of the proposed method.

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Periodical:

Advanced Materials Research (Volumes 588-589)

Edited by:

Lawrence Lim

Pages:

1527-1532

Citation:

Y. H. Zhu et al., "NN-Based Adaptive Output Feedback Stabilization via Passivation of MIMO Uncertain System", Advanced Materials Research, Vols. 588-589, pp. 1527-1532, 2012

Online since:

November 2012

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$38.00

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