Adaptive Mechanism Empowers the Fuzzy Control Rule Base——Optimization of Motor Control
As the requirements for motor control performance escalate,the limitations of traditional fuzzy control have become evident.This paper proposes introducing an adaptive mechanism into the fuzzy control rule base.It expounds on the principles including parameter self-adjustment and rule dynamic update.The implementation methods in motor control,such as model reference adaptive and neural network-based adaptive,are elaborated in detail.This mechanism augments the system robustness and control accuracy.The effectiveness is verified through experimental comparison.The results demonstrate that when confronted with motor parameter variations and external interferences,the fuzzy con-trol with adaptive mechanism can render the motor speed more stable and reduce the error.
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