Curriculum-Based Soft Actor-Critic for Multi-Section R2R Tension Control
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arXiv
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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866908856340185088 |
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| author | Li, Shihao Li, Jiachen Martin, Christopher Chen, Zijun Chen, Dongmei Li, Wei |
| author_facet | Li, Shihao Li, Jiachen Martin, Christopher Chen, Zijun Chen, Dongmei Li, Wei |
| contents | Precise tension control in roll-to-roll (R2R) manufacturing is difficult under varying operating conditions and process uncertainty. This paper presents a curriculum-based Soft Actor-Critic (SAC) controller for multi-section R2R tension control. The policy is trained in three phases with progressively wider reference ranges, from 27 to 33 N to the full operating envelope of 20 to 40 N, so it can generalize across nominal and disturbed conditions. On a three-section R2R benchmark, the learned controller achieves accurate tracking in nominal operation and handles large disturbances, including 20 N to 40 N step changes, with a single policy and no scenario-specific retuning. These results indicate that curriculum-trained SAC is a practical alternative to model-based control when system parameters vary and process uncertainty is significant. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_24259 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Curriculum-Based Soft Actor-Critic for Multi-Section R2R Tension Control Li, Shihao Li, Jiachen Martin, Christopher Chen, Zijun Chen, Dongmei Li, Wei Systems and Control Precise tension control in roll-to-roll (R2R) manufacturing is difficult under varying operating conditions and process uncertainty. This paper presents a curriculum-based Soft Actor-Critic (SAC) controller for multi-section R2R tension control. The policy is trained in three phases with progressively wider reference ranges, from 27 to 33 N to the full operating envelope of 20 to 40 N, so it can generalize across nominal and disturbed conditions. On a three-section R2R benchmark, the learned controller achieves accurate tracking in nominal operation and handles large disturbances, including 20 N to 40 N step changes, with a single policy and no scenario-specific retuning. These results indicate that curriculum-trained SAC is a practical alternative to model-based control when system parameters vary and process uncertainty is significant. |
| title | Curriculum-Based Soft Actor-Critic for Multi-Section R2R Tension Control |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2602.24259 |