Design of an optimal fuzzy logic controller using response surface methodology

When the fuzzy logic controller (FLC)-designed based on the plant model-is applied to the real control system, satisfactory control performance may not be attained due to modeling errors from the plant model. Also, a controller that is designed under specific circumstances may not show satisfactory control performance when applied to other circumstances. In such cases, the control parameters of the controller must be adjusted to enhance control performance. Until now, the trial and error method has been used, consuming much time and effort. Also, the set of adjusted values is not guaranteed to be optimal. To resolve such problems, response surface methodology (RSM), a method of adjusting the control parameters of the controller, is suggested. This method is more systematic than the previous trial and error method, thus, optimal solutions can be provided with less tuning. First, the initial values of the control parameters are determined through the plant model and the optimization algorithm. Then designed experiments are performed in the region around the initial values, determining the optimal values of the control parameters that satisfy both the rise time and overshoot simultaneously