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An adaptive neural robust controller was designed by using adaptive backstepping method for a class of nonlinear uncertain chaotic systems which could be turned to "standard block control type", Furthermore, It is possible to make the network more stable and make the selection of simulation parameter more easy due to the introduction of differential reconstruction which increased the damp...
Adaptive neural robust controller was designed by using adaptive backstepping method for a class of unknown chaotic system which could be turned to "standard block control type". It was proved by constructing Lyapunov function step by step that all signals of the system are bounded and exponentially converge to the neighborhood of the origin globally. Finally, simulation study is given to...
Considered both the situation with unknown control function matrices and the situation with linear unmodeled input dynamics, adaptive neural robust controller was designed by using adaptive backstepping method for a class of multi-input to multi-output nonlinear systems which could be turned to "standard block control type". Furthermore, it is possible to make the network more stable and...
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