On-Line Learning of a Time Variant System
In the present work a sliding window approach for the Levenberg-Marquardt algorithm is used for on-line modelling a time variant system. The system used is a first order cruise control in which a modification is introduced to change the system gain at some point of operation. The initial control of the cruise control is performed by a PI not particularly optimised but enough to keep the system working within the intended range, which is then replaced by an Artificial Neural Network as soon as it is trained, using an Internal Model Controller loop.
KeywordsHessian Matrix Trust Region Inverse Model Time Variant System Slide Window Approach
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- 4.Ngia, L.S.H.: System Modeling Using Basis Functions and Application to Echo Cancelation, Ph.D. thesis, Department of Signals and Systems School of Electrical and Computer Engineering, Chalmers University of Technology (2000)Google Scholar
- 6.Dias, F.M., Antunes, A., Vieira, J., Mota, A.M.: Implementing the levenberg-marquardt algorithm on-line: A sliding window approach with early stopping. In: 2nd IFAC Workshop on Advanced Fuzzy/Neural Control (2004)Google Scholar
- 7.Morgan, N., Bourlard, H.: Generalization and parameter estimation in feedforward nets: Some experiments. In: Touretzsky, D. (ed.) Advances in Neural Information Processing Systems, pp. 630–637. Morgan Kaufmann, San Francisco (1990)Google Scholar
- 8.Sjöberg, J.: Non-Linear System Identification with Neural Networks, Ph.D. thesis, Dept. of Electrical Engineering, Linköping University, Suécia (1995)Google Scholar
- 9.Dias, F.M., Antunes, A., Mota, A.: A new hybrid direct/specialized approach for generating inverse neural models. WSEAS Transactions on Systems 3(4), 1521–1529 (2004)Google Scholar
- 10.Nørgaard, M.: Neural network based system identification toolbox for use with matlab, version 1.1, technical report. Tech. Rep. Technical University of Denmark (1996)Google Scholar
- 11.Nørgaard, M.: Neural network based control system design toolkit for use with matlab, version 1.1, technical report. Tech. Rep., Technical University of Denmark (1996)Google Scholar