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1 International Journal of Applied Mathematics and Computer Science

1 2005

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Stabilising solutions to a class of nonlinear optimal state tracking problems using radial basis function networks

Ahmida Z., Charef A., Becerra V. M.

International Journal of Applied Mathematics and Computer Science

2005

Vol. 15, no 3

369-381

A controller architecture for nonlinear systems described by Gaussian RBF neural networks is proposed. The controller is a stabilising solution to a class of nonlinear optimal state tracking problems and consists of a combination of a state feedback stabilising regulator and a feedforward neuro-controller. The state feedback stabilising regulator is computed online by transforming the tracking problem into a more manageable regulation one, which is solved within the framework of a nonlinear predictive control strategy with guaranteed stability. The feedforward neuro-controller has been designed using the concept of inverse mapping. The proposed control scheme is demonstrated on a simulated single-link robotic manipulator.