Identification and Adaptive Control of a Coordinate Measuring Machine

Important factors in manufacturing are quality and cost. Measuring machines play an important role for these fields. In order to meet higher demands on cost and accuracy, measuring machines can be constructed with weaker materials and increased mechanical flexibilities, and therefore there is a need to include the flexibilities in measuring machine models to obtain good performance. The core theme in this thesis is modeling and idenfication of the physical parameters of drive mechanisms of a Brown&Sharpe Inc. Global A coordinate measuring machine. The approximation made is that the drive mechanisms can be described by a mass connected by springs, dampers and gear changes. It has been found that a one-spring model gives a reasonably good description of the studied CMM drive mechanism. The physical parameters of this model are identified using off-line algorithms. The algorithms are based on prediction error methods. For the off-line identification the MATLAB System Identification Toolbox and the bond graph representation is used. The chosen model is then used for control. Traditional control and a Model-reference Adaptive System is derived and studied with the aim to increase the damping of CMM drive mechanisms. It is found that the adaptive system has very good disturbance rejection and can correct for drastic model errors. Another impact is that the damping of the studied drive mechanism can be increased with at least a factor of nine