An IMC based Fuzzy Self-Tuning Mechanism for Fuzzy PID Controllers

In this study, we will present a novel Internal Model Control (IMC) based Self-Tuning (ST) mechanism to tune the Scaling Factors (SFs) of the fuzzy PID controllers in an online manner. Moreover, we will present a fuzzy PI-D (FPI-D) structure in order to eliminate the derivative kick and the effect of noise on the control signal. The proposed IMC based fuzzy ST mechanism is constructed by two Fuzzy Inference Systems (FISs) and an IMC based SF (IMC-SF) parameter regulator. The two FISs will predict the current values of the system parameters by using the system output value and then the IMC-SF parameter regulator will tune the SFs of FPI-D with respect to presented tuning method. The performance of the proposed Self-Tuning FPI-D (ST-FPI-D) will be evaluated on a real-time laboratory scale extruder process with its discrete implementation via the ABB PLC PM573 industrial controller. We will compare and examine the control system performance of the proposed ST fuzzy control structure with an IMC based tuned ABB-PID and FPI-D structures. The real-time experimental results will show that the proposed ST-FPI-D structure enhanced significantly the control performance for various operating points and in the presence of uncertainties and nonlinearities when compared to the ABB-PID and FPI-D structures.