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The problem considered in the paper is anti-control of chaos for a non-chaotic system via a fuzzy neural network inverse system (FNNIS) method. A Sugeno type fuzzy neural network (FNN) is trained to learn the kinetics of the non-chaotic system. The trained FNN model is employed in the inverse system method, thereby, the exact mathematic model of the system to be controlled is not necessary. The FNN model error upon control is studied and a related theorem is developed. Simulation results for continuous and discrete systems show the effectiveness of the method.