Input/Output Stability Theory For Direct Neuro-Fuzzy Controllers
Input/Output Stability Theory For Direct Neuro-Fuzzy Controllers
Within the framework of input/output stability we develop an algorithm for testing the stability of a given direct, static, multiple-input, single-output, neuro-fuzzy controller operating under feedback control, dependant only on the functional gain of the plant to be controlled. It is shown that various stability regions in weight space are convex, and necessary and sufficient conditions are given for these stability regions to be open and bounded. The convexity results coupled with the stability test gives a practical method for constructing the stability regions. We show that an adaptive neuro-fuzzy controller is stable under feedback if we constrain the weights of the controller to lie within any compact set within the stability region. Combining a projection operator with any standard training law can thus give a stable adaptive controller.
331-345
French, M
22958f0e-d779-4999-adf6-2711e2d910f8
Rogers, E
611b1de0-c505-472e-a03f-c5294c63bb72
1998
French, M
22958f0e-d779-4999-adf6-2711e2d910f8
Rogers, E
611b1de0-c505-472e-a03f-c5294c63bb72
French, M and Rogers, E
(1998)
Input/Output Stability Theory For Direct Neuro-Fuzzy Controllers.
IEEE Transactions on Fuzzy Systems, 6 (3), .
Abstract
Within the framework of input/output stability we develop an algorithm for testing the stability of a given direct, static, multiple-input, single-output, neuro-fuzzy controller operating under feedback control, dependant only on the functional gain of the plant to be controlled. It is shown that various stability regions in weight space are convex, and necessary and sufficient conditions are given for these stability regions to be open and bounded. The convexity results coupled with the stability test gives a practical method for constructing the stability regions. We show that an adaptive neuro-fuzzy controller is stable under feedback if we constrain the weights of the controller to lie within any compact set within the stability region. Combining a projection operator with any standard training law can thus give a stable adaptive controller.
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Published date: 1998
Organisations:
Southampton Wireless Group
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Local EPrints ID: 250132
URI: http://eprints.soton.ac.uk/id/eprint/250132
PURE UUID: e96838ff-c867-4c1f-b5ff-b1f014a4a13e
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Date deposited: 08 Mar 2004
Last modified: 09 Jan 2022 02:40
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Author:
M French
Author:
E Rogers
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