A systematic and simple approach for designing Takagi-Sugeno fuzzy controller with reduced data

This paper introduces a simple, systematic and effective method for designing Takagi-Sugeno (T-S) fuzzy controller utilizing a significantly small training data. Creating proper training data is not an easy task and requires spending considerable time and resources. The proposed method first uses the three-level factorial design to partition the input space. Next the response surface methodology (RSM) is used to estimate the output spaces. The membership functions are introduced with only three variables (min, max and number of membership functions). Fuzzy rules are generated with respect to the output surfaces and membership functions. The proposed method is applied for controlling an inverted pendulum. Simulation results demonstrate significant improvement for controlling the inverted pendulum.