Rejecting Multiplicative Input Disturbance Using Fuzzy Model-Free Adaptive Control

Disturbance rejection is one of the most challenging issues when the system under control is nonlinear and little a priori information is available about the system. Internal model control (IMC) has been extensively used for disturbance rejection but has certain drawbacks. Most of the work reported in literature deals with additive output disturbance. The main focus of this study is on multiplicative input disturbance. In this work, fuzzy model-free adaptive control (FMAC) is used to reject the disturbance in an uncertain nonlinear plant. Different schemes have been investigated for rejecting the disturbance. It is demonstrated that the particular type of disturbance cannot be completely rejected using the IMC. The second methodology used to reject the disturbance is feedforward of the measured disturbance. Feedforward of the input disturbance is used which is able to counteract the effect of the disturbances but resulting in an increase in the control activity. The control activity is related to the noise on the sensor measuring the input disturbance. The FMAC is modelled as a fuzzy relational model (FRM) which is able to represent the noise level in the fuzzy control signal. Conditional defuzzification is applied on the resulting fuzzy control signal; which is able to reduce the control activity while maintaining the controlled output at the desired level. FMAC is tested with a modified version of the Hammerstein Model. The control performance demonstrates the effectiveness of the proposed novel methodology in rejecting the input multiplicative disturbance while reducing the control activity.