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Hessian Matrix Estimation in Hybrid Systems Based on an Embedded FFNN.
- Source :
-
IEEE Transactions on Neural Networks . Oct2010, Vol. 21 Issue 10, p1533-1542. 10p. - Publication Year :
- 2010
-
Abstract
- This paper describes the Hessian matrix estimation of nonsmooth nonlinear parameters by the identifier based on a feedforward neural network (FFNN) embedded in a hybrid system, which is modeled by the differential–algebraic–impulsive–switched (DAIS) structure. After identifying full dynamics of the hybrid system, the FFNN is used to estimate second-order derivatives of an objective function \bf J with respect to the nonlinear parameters from the gradient information, which are trajectory sensitivities. Then, the estimated Hessian matrix is applied to the optimal tuning of a saturation limiter used in a practical engineering system. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 10459227
- Volume :
- 21
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Neural Networks
- Publication Type :
- Academic Journal
- Accession number :
- 54290197
- Full Text :
- https://doi.org/10.1109/TNN.2010.2042728