A disturbance attenuating adaptive neural network controller for multi-input nonlinear systems

作者: Artemis K. Kostarigka , George A. Rovithakis

DOI: 10.23919/ECC.2007.7068307

关键词: Small setNonlinear systemDynamical systems theoryZero (complex analysis)Control theoryDivision by zeroMathematicsTracking errorAffine transformationUniform boundedness

摘要: An adaptive neural network controller for multi-input nonlinear, affine in the control dynamical systems with unknown nonlinearities is designed, capable of attenuating L 2 ,L ∞ external disturbances. In absence disturbances, a uniform ultimate boundedness property tracking error respect to an arbitrarily small set around origin guaranteed, as well all signals closed loop. Possible division by zero avoided use novel resetting procedure, guaranteeing away from certain signals. Simulations illustrate approach.

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