Please use this identifier to cite or link to this item:
|Title:||A New Time-Efficient Structure for Observer-Based Adaptive Fuzzy-Neural Controllers for Nonaffine Nonlinear Systems|
|Abstract:||This paper proposes an observer-based adaptive controller with a merged fuzzy-neural network for nonaﬃne nonlinear systems under the constraint that only the system output is available for measurement. Using a conventional fuzzy-neural network leads to rule explosion which leads to huge computation time. Our proposed merged-FNN does not have this problem, and can take the place of the conventional fuzzy-neural networks under some assumptions while maintaining the property of stability. Moreover, the adaptive scheme using the merged-FNN guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. Finally, this paper gives examples of the proposed controller for nonaﬃne nonlinear systems, and is shown to provide good eﬀectiveness.|
|Appears in Collections:||教師著作|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.