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Optimal Robust Tracking Control of Injection Velocity in an Injection Molding Machine

Author

Listed:
  • Guoshen Wu

    (Guangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou 510006, China)

  • Zhigang Ren

    (Guangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou 510006, China
    Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing, Guangdong University of Technology, Guangzhou 510006, China)

  • Jiajun Li

    (Guangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou 510006, China
    Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing (GDUT), Ministry of Education, Guangzhou 510006, China)

  • Zongze Wu

    (Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China)

Abstract

Injection molding is a critical component of modern industrial operations, and achieving fast and stable control of injection molding machines (IMMs) is essential for producing high-quality plastic products. This paper focuses on solving an optimal tracking control problem of the injection velocity that arises in a typical nonlinear IMM. To this end, an efficient optimal robust controller is proposed and designed. The nonlinear injection velocity servo system is first approximately linearized at iteration points using the first-order Taylor expansion approach. Then, at each time node in the optimization process, the relevant algebraic Riccati equation is introduced, and the solution is used to construct an optimal robust feedback controller. Furthermore, a rigorous Lyapunov theorem analysis is employed to demonstrate the global stability properties of the proposed feedback controller. The results from numerical simulations show that the proposed optimal robust control strategy can successfully and rapidly achieve the best tracking of the intended injection velocity trajectory within a given time.

Suggested Citation

  • Guoshen Wu & Zhigang Ren & Jiajun Li & Zongze Wu, 2023. "Optimal Robust Tracking Control of Injection Velocity in an Injection Molding Machine," Mathematics, MDPI, vol. 11(12), pages 1-17, June.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:12:p:2619-:d:1166565
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    References listed on IDEAS

    as
    1. Mohammad Reza Khosravani & Sara Nasiri, 2020. "Injection molding manufacturing process: review of case-based reasoning applications," Journal of Intelligent Manufacturing, Springer, vol. 31(4), pages 847-864, April.
    2. repec:taf:nmcmxx:v:24:y:2018:i:5:p:431-454 is not listed on IDEAS
    3. Christoph Froehlich & Wolfgang Kemmetmüller & Andreas Kugi, 2018. "Control-oriented modeling of servo-pump driven injection molding machines in the filling and packing phase," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 24(5), pages 451-474, September.
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