Robust hybrid T1/IT2 fuzzy PIDD 2 controllers for AVR systems under parameter uncertainties and challenging operating conditions

This study proposes two hybrid controllers—namely the Type-1 Fuzzy PIDD2 (T1FPIDD2) and the Interval Type-2 Fuzzy PIDD2 (IT2FPIDD2)—for the stable and reliable regulation of Automatic Voltage Regulator (AVR) systems across a wide range of system parameters, including highly adverse and worst-case operating conditions. The proposed control schemes combine the PIDD2 controller, which is well recognised in AVR applications for its favourable performance, with fuzzy inference mechanisms to enhance robustness and dynamic response. The controller parameters are determined under nominal system conditions using the Equilibrium Optimiser (EO) algorithm. Performance evaluation is carried out by comparing the proposed hybrid controllers with the standalone PIDD2 controller, first under nominal system parameters and subsequently under the maximum parameter values reported in the literature. In addition, the controller responses are examined under various disturbance scenarios, including generator frequency deviations, sudden load variations, and short-circuit faults. Robustness tests are further performed to assess controller behaviour under degraded system parameters. The simulation results demonstrate that the standalone PIDD2 controller fails to maintain system stability under extreme parameter conditions, whereas the fuzzy-enhanced hybrid controllers provide effective and stable AVR regulation, exhibiting improved tolerance to uncertainties and large-scale parameter variations.