Multilayer feedforward networks are universal approximators
Neural Networks
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Robust adaptive control
Direct adaptive fuzzy output tracking control of nonlinear systems
Fuzzy Sets and Systems - Featured Issue: Selected papers from ACIDCA 2000
Observer-based adaptive fuzzy-neural control for unknown nonlineardynamical systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Stable adaptive control using fuzzy systems and neural networks
IEEE Transactions on Fuzzy Systems
Adaptive fuzzy-based tracking control for nonlinear SISO systems via VSS and H∞ approaches
IEEE Transactions on Fuzzy Systems
A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems
IEEE Transactions on Fuzzy Systems
Fuzzy adaptive sliding-mode control for MIMO nonlinear systems
IEEE Transactions on Fuzzy Systems
Observer design for a class of MIMO nonlinear systems
Automatica (Journal of IFAC)
Output feedback control of nonlinear systems using RBF neural networks
IEEE Transactions on Neural Networks
Neural-network control of nonaffine nonlinear system with zero dynamics by state and output feedback
IEEE Transactions on Neural Networks
Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems
IEEE Transactions on Neural Networks
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In this paper, an indirect adaptive fuzzy output-feedback control based on the observer is presented for Single-Input Single-Output (SISO) uncertain non-linear systems. On the basis of the estimation of the tracking error, and without resorting to the famous Strictly Positive Real condition or the filtering of the observation error, a Proportional-Integral law for updating the adjustable parameters is proposed. Then, a unified observer is used to estimate the tracking error. Indeed, the corrective term of the proposed observer involves a well-defined design function which is shown to be satisfied by the commonly used High-Gain (HG)-based observers, namely, for the usual HG observers and the Sliding Modes observers together with their implementable versions. The Lyapunov synthesis approach is used to guarantee a Uniformly Ultimately Bounded property of the observation and tracking errors, as well as of all other signals in a closed-loop system. The viability and the efficiency of the obtained fundamental results are clearly illustrated through a numerical simulation involving the usual benchmark example of the fuzzy control community.