Robust adaptive control
A dynamic recurrent neural-network-based adaptive observer for a class of nonlinear systems
Automatica (Journal of IFAC)
Fuzzy Sets and Systems - Theme: Fuzzy control
Observer-based robust fuzzy control of nonlinear systems with parametric uncertainties
Fuzzy Sets and Systems - Modeling and control
Stable indirect fuzzy adaptive control
Fuzzy Sets and Systems - Theme: Modeling and control
Observer-based adaptive fuzzy-neural control for unknown nonlineardynamical systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive fuzzy sliding mode control of nonlinear system
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Adaptive output feedback control of nonlinear systems using neural networks
Automatica (Journal of IFAC)
New approaches to H∞ controller designs based on fuzzy observers for T-S fuzzy systems via LMI
Automatica (Journal of IFAC)
Further results on adaptive control for a class of nonlinear systems using neural networks
IEEE Transactions on Neural Networks
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This paper proposes a new ouput-feedback adaptive fuzzy controller for SISO affine nonlinear systems. The previous output-feedback control algorithms are all based on the state observer (e.g., higher-order-observer) or additional low-pass filter to make the estimation error dynamics SPR, which makes the stability analysis of the closed-loop system and real implementation very complicated. The distingushied aspect of the proposed output-feedback control algorithm is that no state observer or low-pass filter is employed. Only the output error is used to generate control input and update laws for unknown fuzzy parameters. The stability analysis depends heavily on the universal function approximation property of the fuzzy system to estimate unknown function of the desired control input. It is shown that, combining this simple output-feedback control algorithm with an online self-structuring fuzzy system, the Lyapunov stability of the closed-loop system is globally guarnateed.