This application discloses an
exoskeleton position prediction and closed-loop
stepper control system and method. The
microcontroller unit completes the functions of
electromyography (EMG)
signal acquisition, neural network
inference, pulse generation, and closed-loop correction. The EMG
signal acquisition unit acquires surface EMG signals, performs preprocessing and
feature extraction, and outputs digital EMG features. The motor position feedback unit acquires the absolute position and velocity information of the closed-loop
stepper motor in real time. The neural network operation unit concatenates the digital EMG features and the absolute position and velocity information of the closed-loop
stepper motor into a multi-dimensional input vector to predict the three-dimensional spatial position increment of the
exoskeleton at the next moment. The dual closed-
loop control unit converts the predicted value of the three-dimensional spatial position increment into
stepper motor control commands and performs closed-loop correction in combination with the real-time position of the motor. Zero-
delay tracking control is achieved through a predictive-execution
parallel pipeline, realizing high-precision, low-
delay tracking of
exoskeleton movement and achieving high
system integration and lightweight design.