Passivity Analysis of Dynamic Neural Networks with Different Time-scales
Neural Processing Letters
Brief paper: An adaptive neuro-fuzzy tracking control for multi-input nonlinear dynamic systems
Automatica (Journal of IFAC)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Neural Networks
A DSC approach to robust adaptive NN tracking control for strict-feedback nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Neuro-adaptive force/position control with prescribed performance and guaranteed contact maintenance
IEEE Transactions on Neural Networks
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This work presents a neural network control redesign, which achieves robust stabilization in the presence of unmodeled dynamics restricted to be input to output practically stable (IOpS), without requiring any prior knowledge on any bounding function. Moreover, the state of the unmodeled dynamics is permitted to go unbounded provided that the nominal system state and/or the control input also go unbounded. The neural network controller is equipped with a resetting strategy to deal with the problem of possible division by zero, which may appear since we consider unknown input vector fields with unknown signs. The uniform ultimate boundedness of the system output to an arbitrarily small set, plus the boundedness of all other signals in the closed-loop is guaranteed.