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Fuzzy rule base and fuzzy variables are two crucial factors which decide the fuzzy controller performance. This paper presents the gradient descent learning algorithm to adaptively optimize free parameters of the interval type-2 fuzzy controller, which can overcome the divergence of another global optimization algorithms, such as GA, PSO and ACO, when they are employed to optimize the free parameters. A few numerical experiments are performed to evaluate our proposing approach. The experiment results verify the effectiveness.