Abstract
Robust sensing and control in fine positioning is a key technology in the presence of various disturbances. For example, the position accuracy of high performance motion control systems is adversely affected by vibrations due to compliance and nonlinear effects such as friction. This paper focuses on a robust friction sensingmethodology based on the sensor fusion via the neural network from AE (acoustic emission) sensors and the feedforward control for the compensation of friction. This compensation is found to be useful for positioning control when frictions applied to the system are adequately and robustly estimated. Encouraging transient response and steady-state control performance were observed in the experimental results of positioning control of a one-dimensional transmission mechanism. The proposed friction sensing and feedforward control can be applied without modifications for nanoscale positioning.
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