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Neural feedback linearization adaptive control for affine nonlinear systems based on neural network estimator

Author(s): Bahita Mohamed | Belarbi Khaled

Journal: Serbian Journal of Electrical Engineering
ISSN 1451-4869

Volume: 8;
Issue: 3;
Start page: 307;
Date: 2011;
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Keywords: adaptive control | control gain estimation | feedback linearization | radial basis function network

In this work, we introduce an adaptive neural network controller for a class of nonlinear systems. The approach uses two Radial Basis Functions, RBF networks. The first RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are unknown. The second RBF network is used for on-line estimating the control gain which is a nonlinear and unknown function of the states. The updating laws for the combined estimator and controller are derived through Lyapunov analysis. Asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, the proposed method is applied to control and stabilize the inverted pendulum system.
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