Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Robust backstepping control of a class of nonlinear systems using fuzzy logic
Information Sciences: an International Journal - Special issue analytical theory of fuzzy control with applications
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Robust and adaptive backstepping control for nonlinear systems using fuzzy logic systems
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Robust adaptive fuzzy control for uncertain nonlinear systems
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Adaptive and robust controller design for uncertain nonlinear systems via fuzzy modeling approach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Robust fuzzy control of nonlinear systems with parametric uncertainties
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Neural Networks
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Adaptive dynamic surface fuzzy control approach is proposed for a class of uncertain nonlinear systems in strict-feedback form. The dynamic surface control technique is introduced to overcome the problem of explosion of terms associated with backstepping design method. Fuzzy logic system is used as a universal approximator to approximate unstructured uncertain functions and the bounds of the reconstruction error is estimated online. The algorithm has the adaptive mechanism with minimum learning parameterizations. Furthermore, all the signals in the closed-loop systems are guaranteed to be semi-globally uniformly ultimately bounded and the output of the system is proved to converge to a small neighborhood of the desired trajectory. The control performance can be guaranteed by an appropriate choice of the design parameters. Simulation results demonstrate the effectiveness of the proposed control method.