Universal approximation using radial-basis-function networks
Neural Computation
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
A dynamic recurrent neural-network-based adaptive observer for a class of nonlinear systems
Automatica (Journal of IFAC)
Adaptive fuzzy control of a class of SISO nonaffine nonlinear systems
Fuzzy Sets and Systems
Automatica (Journal of IFAC)
Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems
Information Sciences: an International Journal
Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive robust fuzzy control of nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy adaptive sliding-mode control for MIMO nonlinear systems
IEEE Transactions on Fuzzy Systems
Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems
IEEE Transactions on Neural Networks
Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
An adaptive fuzzy control algorithm is designed for a class of uncertain nonlinear nonaffine systems. Fuzzy logic systems are used to approximate unknown nonlinear functions. In contrast to the previous results of nonlinear nonaffine systems, a main advantage is that it does not require a priori knowledge about the sign of the control gain coefficient. It can be proven that the closed-loop system is stable in the sense that all the signals are bounded and the system output track the reference signal to a small neighborhood of the origin by appropriately choosing design parameters.