Model predictive force control in five-axis positional milling using a table dynamometer

Abstract Milling is a highly flexible and productive machining process characterized by an intermittent tool-workpiece engagement. To further increase productivity, several force control strategies have been proposed to maintain a constant load on the milling tool for arbitrary engagement conditions. One example is model predictive force control (MPFC), which is attractive for milling because it achieves high control performance without requiring calibration experiments. However, so far it has been limited to three-axis milling. Machining processes for complex components like Blisks (bladed disks) require additional degrees of freedom, referred to as multi-axis synchronous milling. Multi-axis milling poses a sensing challenge: Table rotations disturb the force measurement of conventional table dynamometers. In this contribution, we propose an MPFC for five-axis positional milling (also referred to as 3+2-axis milling) as an intermediate step towards five-axis synchronous milling. We use an inverted measurement model to compensate for rotational disturbances and introduce a novel method to identify the angular position of the milling tool with maximum engagement for each position along the tool path in five-axis positional milling. Adaptations in the generation of the position-dependent reference and careful parameter tuning enable the control scheme to optimize the feed velocity without exceeding the computation time. The proposed method for approximating the maximum engagement is applicable to both three-axis and five-axis positional milling. In five-axis positional milling, it reduces the mean absolute force error from 42.6 N achieved with an established approximation to 1.2 N. In an experimental machining operation, the MPFC reduced machining time by 67 % compared with the manufacturer’s recommended feed velocity, without substantially increasing the maximum tool load, and achieved a median absolute force-tracking deviation of only 10.3 N. Overall, these results demonstrate that the MPFC can be transferred from three-axis to five-axis positional milling while maintaining high control performance, representing an intermediate step towards application in five-axis synchronous milling.

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Publication Details

Journal
Journal of Intelligent Manufacturing
Published
2026-05-22
DOI
https://doi.org/10.1007/s10845-026-02875-7
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Model predictive force control in five-axis positional milling using a table dynamometer

Heike Vallery, Sebastian Stemmler, Patrick Ochudlo, Lorenz Schmidt et al.
Journal of Intelligent Manufacturing
Advanced machining processes and optimization
article

Model predictive force control in five-axis positional milling using a table dynamometer

Heike Vallery, Sebastian Stemmler, Patrick Ochudlo, Lorenz Schmidt, Thomas Bergs, Adrian Karl Rueppel
article en

Abstract

Abstract Milling is a highly flexible and productive machining process characterized by an intermittent tool-workpiece engagement. To further increase productivity, several force control strategies have been proposed to maintain a constant load on the milling tool for arbitrary engagement conditions. One example is model predictive force control (MPFC), which is attractive for milling because it achieves high control performance without requiring calibration experiments. However, so far it has been limited to three-axis milling. Machining processes for complex components like Blisks (bladed disks) require additional degrees of freedom, referred to as multi-axis synchronous milling. Multi-axis milling poses a sensing challenge: Table rotations disturb the force measurement of conventional table dynamometers. In this contribution, we propose an MPFC for five-axis positional milling (also referred to as 3+2-axis milling) as an intermediate step towards five-axis synchronous milling. We use an inverted measurement model to compensate for rotational disturbances and introduce a novel method to identify the angular position of the milling tool with maximum engagement for each position along the tool path in five-axis positional milling. Adaptations in the generation of the position-dependent reference and careful parameter tuning enable the control scheme to optimize the feed velocity without exceeding the computation time. The proposed method for approximating the maximum engagement is applicable to both three-axis and five-axis positional milling. In five-axis positional milling, it reduces the mean absolute force error from 42.6 N achieved with an established approximation to 1.2 N. In an experimental machining operation, the MPFC reduced machining time by 67 % compared with the manufacturer’s recommended feed velocity, without substantially increasing the maximum tool load, and achieved a median absolute force-tracking deviation of only 10.3 N. Overall, these results demonstrate that the MPFC can be transferred from three-axis to five-axis positional milling while maintaining high control performance, representing an intermediate step towards application in five-axis synchronous milling.

Journal of Intelligent Manufacturing
Deutsche Forschungsgemeinschaft
Decent work and economic growth
Openalex Percentile: Top 10%
Advanced machining processes and optimization
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