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A new dynamical fuzzy modeling and control for SISO complex systems

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conference contribution
posted on 2024-07-12, 17:08 authored by Zhihong ManZhihong Man, Xinghuo Yu, Xiaojiang Zhang, Shiyu Gao
In this paper, we propose a new dynamical fuzzy modeling technique for SISO complex systems. It is seen that, the whole state-space of a complex system is divided into subspaces and a linear time-invariant (LTI) model is then used to approximate the complex system in each subspace. However, the global dynamical fuzzy model of the complex system is derived by aggregating all subsystem poles and zeros using the weighted average fuzzy inference approach instead of aggregating all subsystem parameter matrices. The motivation of such a modeling technique is to make the system and its global dynamical fuzzy model have the same stability property. The eigenstructure-assignment for linear time varying (LTV) systems and sliding mode control technique are then used to design a controller to stabilize the new global dynamical fuzzy system. A simulation example is given in support of the new dynamical fuzzy modeling and control.

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ISBN

9780780379060

Journal title

Proceedings of the 29th IEEE Industrial Electronics Conference (IECON 2003), Roanoke, Virginia, United States, 02-06 November 2003

Conference name

The 29th IEEE Industrial Electronics Conference IECON 2003, Roanoke, Virginia, United States, 02-06 November 2003

Volume

3

Pagination

5 pp

Publisher

IEEE

Copyright statement

Copyright © 2003 IEEE. The published version is reproduced in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Language

eng

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