Transformation-based iterative learning control for non-collocated sensing of a galvanometer scanner

A transformation-based iterative learning control (ILC) approach is proposed to achieve accurate image scanning for the non-collocated dynamics of a galvanometer scanner. The non-collocation between the encoder and beam scanning mirror results in a tracking error of the actual beam position although the encoder measurement matches the reference signal. The proposed ILC is extended from the conventional ILC design by adding a reference transformation filter, which is based on the transfer functions between the measured and the controlled output. An error analysis shows that the proposed method can reduce the error of the actual controlled output, especially for applications of a large tracking reference such as image scanning. Experimental results with the proposed ILC show a better tracking accuracy as compared to conventional ILC design with non-collocated sensing.