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A type-2 fuzzy neural system (T2FNS) is proposed in this paper for process control. The structure of the system is presented and the rules for updating its parameters are derived using the gradient algorithm. The effectiveness of the proposed approach is evaluated on a laboratory setup that regulates the speed of a DC motor and the experimental results are compared with those obtained with the use of a type-1 fuzzy neural system (T1FNS). It is seen that T2FNS results in reduced oscillations around the set point in the presence of load disturbances.