Design of Direct Torque Control with Fuzzy Control Implementation

In this paper, we present a design methodology for direct torque control incorporating fuzzy logic control. Compared to traditional PI regulators, this approach demonstrates several significant advantages. Firstly, fuzzy control exhibits superior adaptability to system nonlinearities, enabling more precise and stable control outcomes. From an implementation perspective, fuzzy controllers utilize membership functions and rule bases that can be programmed using conditional statements and lookup tables in control algorithms. Secondly, the fuzzy control system offers flexibility through adjustable fuzzy rules and membership functions, allowing adaptation to various operating conditions and environmental changes without structural controller modifications. This can be implemented through parameter tuning functions in the control code. Finally, fuzzy control demonstrates enhanced capability in handling system uncertainties and noise interference, thereby improving overall system robustness and disturbance rejection. The fuzzy inference engine typically employs methods like Mamdani or Sugeno models, which can be coded using weighted average calculations and defuzzification techniques. Consequently, direct torque control with fuzzy logic implementation shows substantial potential and advantages across numerous application domains.