Multilayer feedforward networks are universal approximators
Neural Networks
Decoupled sliding-mode with fuzzy-neural network controller for nonlinear systems
International Journal of Approximate Reasoning
Robust sliding mode control based wind power generation
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
Indirect sliding mode neural-network control for holonomic constrained robot manipulators
International Journal of Intelligent Systems Technologies and Applications
Type-2 fuzzy sliding mode control without reaching phase for nonlinear system
Engineering Applications of Artificial Intelligence
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This paper develops a method for neural network control design with sliding modes in which robustness is inherent. Neural network control is formulated to become a class of variable structure (VSS) control. Sliding modes are used to determine best values for parameters in neural network learning rules, thereby robustness in learning control can be improved. A switching manifold is prescribed and the phase trajectory is demanded to satisfy both, the reaching condition and the sliding condition for sliding modes.