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Real-Time Regulation of Direct Ink Writing Using Model Reference Adaptive Control

Mandana Mohammadi Looey, Amrita Basak, Satadru Dey

Abstract

Direct Ink Writing (DIW) has gained attention for its potential to reduce printing time and material waste. However, maintaining precise geometry and consistent print quality remains challenging under dynamically varying operating conditions. This paper presents a control-focused approach using a model reference adaptive control (MRAC) strategy based on a reduced-order model (ROM) of extrusion-based 3D printing for a candidate cementitious material system. The proposed controller actively compensates for uncertainties and disturbances by adjusting process parameters in real time, with the objective of minimizing reference-tracking errors. Stability and convergence are rigorously verified via Lyapunov analysis, demonstrating that tracking errors asymptotically approach zero. Performance evaluation under realistic simulation scenarios confirms the effectiveness of the adaptive control framework in maintaining accurate and robust extrusion behavior.

Real-Time Regulation of Direct Ink Writing Using Model Reference Adaptive Control

Abstract

Direct Ink Writing (DIW) has gained attention for its potential to reduce printing time and material waste. However, maintaining precise geometry and consistent print quality remains challenging under dynamically varying operating conditions. This paper presents a control-focused approach using a model reference adaptive control (MRAC) strategy based on a reduced-order model (ROM) of extrusion-based 3D printing for a candidate cementitious material system. The proposed controller actively compensates for uncertainties and disturbances by adjusting process parameters in real time, with the objective of minimizing reference-tracking errors. Stability and convergence are rigorously verified via Lyapunov analysis, demonstrating that tracking errors asymptotically approach zero. Performance evaluation under realistic simulation scenarios confirms the effectiveness of the adaptive control framework in maintaining accurate and robust extrusion behavior.
Paper Structure (10 sections, 2 theorems, 18 equations, 7 figures, 1 table)

This paper contains 10 sections, 2 theorems, 18 equations, 7 figures, 1 table.

Table of Contents

  1. Introduction
  2. Problem Statement: Control of Extrusion-based 3D Printing Processes
  3. Basic Architecture
  4. Control-Oriented Model of Extrusion-Based Printing
  5. Adaptive Control Problem in Extrusion-Based Printing
  6. Adaptive Control Framework for Extrusion-based 3D Printing Processes
  7. Adaptive Control Architecture
  8. Model Reference Adaptive Control Design and Analysis
  9. Results and Discussion
  10. Conclusions

Key Result

Proposition 1

Consider the extrusion-based 3D printing system described by romre-1-romre-3, the state feedback control law sfb-3, the parameter adaptation law ad-3, and the reference model rm-3. Then, the reference model tracking error signals $e_1 \triangleq \bar{v}_1 - {v_r}_1$ and $e_3 \triangleq \bar{u}_3 - {

Figures (7)

  • Figure 1: Schematic of the extrusion-based 3D printing process including three sub-systems.
  • Figure 2: A schematic of model reference adaptive control of extrusion-based 3D printing process.
  • Figure 3: Probability distribution of modeling error.
  • Figure 4: Responses from Case Study 1: Tracking performance under plate velocity disturbance.
  • Figure 5: Responses from Case Study 2: Tracking performance under inlet mass flow disturbance.
  • ...and 2 more figures

Theorems & Definitions (6)

  • Remark 1
  • Proposition 1: Boundedness of reference model tracking and parameter estimation error signals
  • proof
  • Proposition 2: Asymptotic stability of reference model tracking and parameter estimation error signals
  • proof
  • Remark 2