Optimal Robust Tracking Control of Injection Velocity in an Injection Molding Machine
Guoshen Wu,
Zhigang Ren (),
Jiajun Li and
Zongze Wu
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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
Jiajun Li: Guangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, 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
Mathematics, 2023, vol. 11, issue 12, 1-17
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.
Keywords: discrete manufacturing process; injection molding; optimal control; model-based control; feedback control (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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