Multivariable adaptive neural control based on multimodel emulator for nonlinear square MIMO systems

This work describes multivariable adaptive neural control based on multimodel emulator for nonlinear square MIMO systems. Multimodel approach is an interesting alternative and a powerful tool for modelling and emulating complex processes. This paper deals with the identification of nonlinear MIMO systems employing an uncoupled multimodel. Efficiency of this multimodel for systems emulation is illustrated in a multivariable adaptive neural control schemes. Neither initialization parameter and nor online adaptation are required in this case. The effectiveness of the proposed multimodel emulator and the control design are shown through numerical simulations.

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