Type-2 Fuzzy Logic Controllers offer great capabilities in modeling and handling the effects of real world uncertainties from sensors, actuators and the environment. Nevertheless, the general Type-2 Fuzzy Logic Controllers enormously suffer from high computation cost. To overcome this problem, in this paper, we present a computationally effective Type-2 Fuzzy Logic Controller which uses Interval Type-2 fuzzy sets to capture the control inputs and utilizes the Takagi-Sugeno-Kang technique to render the control outputs. It is shown that the proposed technique greatly reduces the computation cost since only the lower and upper bounds of the input fuzzy sets suffice to calculate the control output.
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