Adaptive wavelet network control design for nonlinear systems

An application of wavelet networks to control problems of nonlinear systems is investigated in this paper. A wavelet network is constructed as an alternative to a neural network to approximate a nonlinear system. Based on this wavelet network approximation, suitable adaptive control laws and appropriate parameter update algorithms for nonlinear uncertain (or unknown) systems are derived to achieve H/sub /spl infin// tracking performance. It is shown that the effects of approximation errors and external disturbances can be attenuated to a specific attenuation level by the proposed adaptive wavelet network control scheme.

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