Metaheuristic-Tuned Type-2 Fuzzy PID Controller for BLDC Motor

In recent trends, Brushless DC motor (BLDC) is becoming an increasingly popular application used in electric engines because of its high productivity, high-velocity activity, robustness, and more modest size. The ripples are caused because of electronic substitution and a viable regulator that is needed to limit the ripples and operate the drives. Adjusting the control factors is too much problematic, consequently, it's challenging to accomplish the ideal state during the real-time environments. Here, the Modified Ziegler and Nichols (MZN) tuning methods are used for PID controllers to adjust the set-point and unmeasured disturbances. In this paper, Adaptive Proportional Integral Derivative- Type-2-Fuzzy Logic Controller named as (MZN-APID- Type-2-FLC) familiar with BLDC engine to reduce the torque ripple and enhance the speed. To further enhance controller performance, a Dandelion optimization algorithm (DOA) is presented for fine-tuning the fuzzy membership functions. The suggested optimized MZN- APID-Type-2-FLC has the capability to assure the control characteristics and makes robustness for performing the operations. From the simulation outcomes, it clearly shows that the proposed optimized MZN-APID-Type-2-FLC achieves the better results in terms of settling time as 0.059s, rise time as 0.01s and overshoot time as 4.05% that is better when compared with existing algorithms namely, ANFIS, Modified PID and Dynamic Power Containment Method (DPCT).