International Journal of Computer Applications in Technology
Intelligent adaptive control for MIMO uncertain nonlinear systems
Expert Systems with Applications: An International Journal
Direct adaptive interval type-2 fuzzy control of multivariable nonlinear systems
Engineering Applications of Artificial Intelligence
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
B-Spline Output Feedback Control for Nonlinear Systems
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Synchronization of uncertain chaotic systems based on adaptive type-2 fuzzy sliding mode control
Engineering Applications of Artificial Intelligence
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ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Adaptive H8 Fuzzy Control for a Class of Uncertain Discrete-Time Nonlinear Systems
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Fuzzy model reference control with adaptation of input fuzzy sets
Knowledge-Based Systems
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A new hybrid direct/indirect adaptive fuzzy neural network (FNN) controller with a state observer and supervisory controller for a class of uncertain nonlinear dynamic systems is developed in this paper. The hybrid adaptive FNN controller, the free parameters of which can be tuned on-line by an observer-based output feedback control law and adaptive law, is a combination of direct and indirect adaptive FNN controllers. A weighting factor, which can be adjusted by the tradeoff between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive FNN controller and direct adaptive FNN controller. Furthermore, a supervisory controller is appended into the FNN controller to force the state to be within the constraint set. Therefore, if the FNN controller cannot maintain the stability, the supervisory controller starts working to guarantee stability. On the other hand, if the FNN controller works well, the supervisory controller will be deactivated. The overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded. Two nonlinear systems, namely, inverted pendulum system and Chua's (1989) chaotic circuit, are fully illustrated to track sinusoidal signals. The resulting hybrid direct/indirect FNN control systems show better performances, i.e., tracking error and control effort can be made smaller and it is more flexible during the design process.