AI & ML
Image-Driven Control with Application to Thermoforming
arXiv cs.SY0 views
arXiv:2611.13256v1 Announce Type: new Abstract: This paper proposes Image-Driven Control (IDC), an approach to vision-based feedback that operates directly in the image space. IDC offers a direct end-to-end solution in the behavioral framework. Targeting a limited subset of vision-based feedback problems, including applications in manufacturing, the IDC design builds on a computationally advantageous subspace predictive control formulation and offset-free tracking to enable reference tracking in the image space under input and pixel-level constraints. IDC provides a control-theoretic alternative to vision-based feedback systems, enabling improved transparency for analysis and tuning of end-to-end control. It offers straightforward experiment design, an advantage in applications where data collection is expensive. The effectiveness of IDC is shown in a simulation example using a nonlinear high-fidelity model of the heating phase of the thermoforming process.
Source:https://arxiv.org/abs/2611.13256PreviousRobust State-Parameter Estimation in Second-Order Th\'evenin BatteriesNextPulsatile Endocrine Regulation with a Releasable Hormone Pool: Impulsive Feedback Model
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