This paper examines an adaptive control scheme for tubular linear motors with micro-metric positioning tolerances. Uncertainties such as friction and other electromagnetic phenomena are approximated with a radial basis function network, which is trained online using a learning law based on Lyapunov design. Differently from related literature, the approximator is trained using a composite adaptation law combining the tracking error and the model prediction error. Stability analysis and bounds for both errors are established, and a report on an extensive experimental investigation is provided to illustrate the practical advantages of the proposed scheme.
Adaptive control with composite learning for tubular linear motors with micro-metric tolerances / Naso, David; Cupertino, Francesco; Turchiano, Biagio. - (2009), pp. 2952-2957. (Intervento presentato al convegno ACC09, IEEE American Control Conference tenutosi a St Louis, Missouri, USA nel June 10-12, 2009) [10.1109/ACC.2009.5159828].
Adaptive control with composite learning for tubular linear motors with micro-metric tolerances
NASO, David;CUPERTINO, Francesco;TURCHIANO, Biagio
2009-01-01
Abstract
This paper examines an adaptive control scheme for tubular linear motors with micro-metric positioning tolerances. Uncertainties such as friction and other electromagnetic phenomena are approximated with a radial basis function network, which is trained online using a learning law based on Lyapunov design. Differently from related literature, the approximator is trained using a composite adaptation law combining the tracking error and the model prediction error. Stability analysis and bounds for both errors are established, and a report on an extensive experimental investigation is provided to illustrate the practical advantages of the proposed scheme.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
