Stable linearization using multilayer neural networksDelgado, A., Kambhampati, C. and Warwick, K. (1996) Stable linearization using multilayer neural networks. In: UKACC International Conference on Control, 2-5 Sep 1996, Exeter, UK, pp. 194-198. Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. Official URL: http://dx.doi.org/10.1049/cp:19960551 Abstract/SummaryThe main limitation of linearization theory that prevents its application in practical problems is the need for an exact knowledge of the plant. This requirement is eliminated and it is shown that a multilayer network can synthesise the state feedback coefficients that linearize a nonlinear control affine plant. The stability of the linearizing closed loop can be guaranteed if the autonomous plant is asymptotically stable and the state feedback is bounded.
Deposit Details University Staff: Request a correction | Centaur Editors: Update this record |