모델 기준 적응 퍼지 제어 시스템의 특성 = A Study on the Characteristics of Model Reference Adaptive Fuzzy Control System

다국어 초록 (Multilingual Abstract)

A Model Reference Adaptive Fuzzy Controller(MRAFC) was proposed in order to overcome the difficuties of extracting rules in the FLC (Fuzzy Logic Controller) and the defect of the adaptation performance in the Model Reference Adaptive Control(MRAC).
The adaptation mechanism make use the information of output error between the plant and the reference model and tunes control rules repeatedly until perfect model following has been met. The control rule modification values were inferenced by relateded information from the output error. For this purpose, a fuzzy model for tuning the control rules was designed based on the magnitude and polarity of following error and velocity of error change. Proposed algorithm was verified through simulations for the various plant models. A DC servo motor was selected for the case study of an actual industrial plant and tested to various loads. The results obtained by using reference model, control rules turned from the learning could be reflected to the overall control system. These rules have shown same features as reference model.
To verify the validity of extracted fuzzy control rules, these were applied to the trajectory following problems for random inputs. The following error was 3.5% and it revealed the possibility that new rules could be applied to the regulator problems and uncertain dynamic systems without new learning process.