The invention relates to the technical field of
servo drivers, in particular to a
servo driver control method, and the technical scheme comprises the steps: carrying out the
online identification of load
inertia and external disturbance through a self-
adaptive observer, generating a dynamic compensation parameter, constructing a multi-model parallel self-
adaptive observer group, and carrying out the
online identification of the load
inertia and external disturbance through the self-
adaptive observer group, a dynamic confidence evaluation mechanism is designed, disturbance dynamic compensation is realized, parameter sudden change and slow change scenes can be taken into consideration, the real-time performance of dynamic response can be ensured, compensation parameters are input into a
fuzzy neural network controller, an
optimal control quantity is generated in combination with a preset control target, a multi-source compensation parameter input channel is constructed, and the
optimal control quantity is generated. A dynamic input weighting module is designed,
fuzzy rule confidence is updated through an
online strategy gradient
algorithm to generate an optimized control quantity, the working condition adaptability can be enhanced, a dynamic target can be dealt with, finally, a sliding mode variable
structure algorithm is adopted to carry out high-frequency buffeting suppression on the control quantity, and a final driving
signal is output to a
power module. And the control precision of the
servo driver is improved.