β Scribed by Shaocheng Tong; Tao Wang; Jian Tao Tang
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
In this paper, a direct adaptive fuzzy-neural output-feedback controller (DAFOC) for a class of uncertain nonlinear systems is developed under the constraint that only the system output is available for measurement. An output feedback control law and an update law are derived for on-line tuning the
An alternative adaptive scheme to achieve output tracking for a class of minimum-phase dynamically input-output linearizable nonlinear systems with parametric uncertainties is considered. The proposed approach is based upon a combination of the adaptive backstepping design method and a sliding mode
An adaptive neuro-fuzzy control design is suggested in this paper, for tracking of nonlinear affine in the control dynamic systems with unknown nonlinearities. The plant is described by a Takagi-Sugeno (T-S) fuzzy model, where the local submodels are realized through nonlinear dynamical input-output
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