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Accurate positioning and fast traversal times determine the productivity inmachining applications. This paper demonstrates a hierarchical contour controlimplementation for the increase of productivity in positioning systems. Thehigh-level controller pre-optimizes the input to a low-level cascadecontroller, using a contouring predictive control approach. This controlstructure requires tuning of multiple parameters. We propose a sample-efficientjoint tuning algorithm, where the performance metrics associated with the fullgeometry traversal are modelled as Gaussian processes and used to form theglobal cost and the constraints in a constrained Bayesian optimizationalgorithm. This approach enables the trade-off between fast traversal, hightracking accuracy, and suppression of vibrations in the system. The performanceimprovement is evaluated numerically when tuning different combinations ofparameters. We demonstrate that jointly tuning the parameters of the contour-and the low-level controller achieves the best performance in terms of time,tracking accuracy, and minimization of the vibrations in the system.

Performance-based Trajectory Optimization for Path Following Control Using Bayesian Optimization