IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Information Sciences: an International Journal
Adaptive robust NN control of nonlinear systems
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
A hierarchical structure of observer-based adaptive fuzzy-neural controller for MIMO systems
Fuzzy Sets and Systems
Interval type 2 hierarchical FNN with the H-infinity condition for MIMO non-affine systems
Applied Soft Computing
Interaction analysis and loop pairing for MIMO processes described by T--S fuzzy models
Fuzzy Sets and Systems
Mutual Synchronization of Multiple Robot Manipulators with Unknown Dynamics
Journal of Intelligent and Robotic Systems
Adaptive control for nonlinear MIMO time-delay systems based on fuzzy approximation
Information Sciences: an International Journal
Fuzzy adaptive backstepping control of a two degree of freedom parallel robot
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
Applications of axiomatic fuzzy sets theory on fuzzy time series forecasting
International Journal of Systems, Control and Communications
State observer based dynamic fuzzy logic system for a class of SISO nonlinear systems
International Journal of Automation and Computing
Adaptive NN control for a class of chemical reactor systems
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
Output feedback adaptive robust NN control for a class of nonlinear discrete-time systems
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
Stability analysis and design of a class of MIMO fuzzy control systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Robust PID TS fuzzy control methodology based on gain and phase margins specifications
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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A robust adaptive fuzzy control approach is developed for a class of multi-input-multi-output (MIMO) nonlinear systems with modeling uncertainties and external disturbances by using both the approximation property of the fuzzy logic systems and the backstepping technique. The MIMO systems are composed of interconnected subsystems in the strict-feedback form. The main characteristics of the developed approach are that the online computation burden is alleviated and the robustness to dynamic uncertainties and external disturbances is improved. It is proven that all the signals of the resulting closed-loop system are uniformly bounded and that the tracking errors converge to a small neighborhood around zero. Two simulation experiments are presented to demonstrate the feasibility of the approach developed in this paper.