Decoupled sliding-mode with fuzzy-neural network controller for nonlinear systems
International Journal of Approximate Reasoning
New adaptive fuzzy sliding-mode control for uncertain non-linear systems
International Journal of Computer Applications in Technology
Ontological approach to development of computing with words based systems
International Journal of Approximate Reasoning
Information Sciences: an International Journal
Historical reflections and new positions on perceptual computing
Fuzzy Optimization and Decision Making
Fuzzy Sets and Systems
Perceptual reasoning for perceptual computing: a similarity-based approach
IEEE Transactions on Fuzzy Systems
Computing with words for hierarchical decision making applied to evaluating a weapon system
IEEE Transactions on Fuzzy Systems - Special section on computing with words
A fuzzy Petri-nets model for computing with words
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Probabilistic automata for computing with words
Journal of Computer and System Sciences
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The rotational/translational proof-mass actuator (RTAC) system is a well-known benchmark for nonlinear control for which a number of controllers were designed. In this paper, we apply fuzzy Lyapunov synthesis, which is a computing with words version of classical Lyapunov synthesis, to design fuzzy controllers for the RTAC system. This allows us to systematically design state-feedback and output-feedback controllers using only a linguistic description of the RTAC system. The designed fuzzy controllers yield a globally asymptotically stable closed-loop system. We demonstrate their advantages in comparison with a previously designed linear controller for the RTAC system.