Disturbance rejection using fuzzy model free adaptive control (FMFAC) with adaptive conditional defuzzification threshold

作者：Kadri Muhammad Bilal^*

来源：Journal of the Franklin Institute, 2014, 351(5): 3013-3031.

DOI：10.1016/j.jfranklin.2014.02.003

Disturbance rejection in nonlinear uncertain systems is a challenging issue especially when the sensor noise cannot be eliminated by low pass filtering. Fuzzy relational models (FRM) can effectively represent the sensor noise in the fuzzy control signal. Due to the large amount of sensor noise there will be huge actuator movement. In most of the cases the actuator movement is in response to the noise and not due to the set-point change. Conditional defuzzification is employed to reduce the control activity. The amount of control activity depends on the threshold level of the conditional defuzzification scheme. A novel scheme has been presented in this paper which can significantly reduce the actuator movement due to noise by adapting the conditional defuzzification threshold. Effective disturbance rejection can be achieved if the controller is modeled as an exact inverse of the plant model. The controller is a fuzzy relational model which develops the inverse plant model by incorporating feedback error learning. Sensitivity analyses have been carried out which demonstrate the efficiency of the proposed methodology.

• 出版日期2014-5