The invention discloses a collimation direct-drive
actuator high-fidelity torque
estimation method based on increment width learning, and belongs to the technical field of
robot actuator torque
estimation, and the method comprises the following steps: S1, collecting multi-dimensional state parameters, and constructing a
data set; s2, obtaining weights of a feature layer and a top layer according to the
data set in the S1, and constructing a basic width learning model; s3, based on the basic width learning model in the S2, when a new
data set is obtained, using an
incremental learning algorithm to update weights of a feature layer and a top layer, and obtaining an updated model; and S4, deploying the model to a torque
control system, and constructing closed-
loop control. By adopting the high-fidelity torque
estimation method for the collimated direct-drive
actuator based on increment width learning, the representation capability can be improved, the estimation precision can be ensured, the training overhead can be reduced, the model can be updated in real time to adapt to dynamic working conditions, high-precision estimation can be realized without an additional
torque sensor, and actuator control can be effectively supported.