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https://doi.org/10.1007/978-3-663-09553-8training algorithm for a modified recurrent high order neural network (RHONN), in order to identify the plant model. Based on this model, a control law is derived, which combines discrete-time block control and sliding mode techniques. The block control approach is used to design a nonlinear sliding
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Schule und Rassismus in den USAng a suitable controller for each subsystem. Accordingly, each subsystem is approximated by an identifier using a discrete-time recurrent high order neural network (RHONN), trained with an extended Kalman filter (EKF) algorithm. The neural identifier scheme is used to model the uncertain nonlinear s
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