Limited Rolling Time Domain-Based Hybrid Tracking Control for Injection Molding Process

被引:3
|
作者
Yu, Jingxian [1 ]
Zhang, Qiyuan [2 ]
机构
[1] Liaoning Shihua Univ, Sch Sci, Fushun 113001, Peoples R China
[2] Liaoning Shihua Univ, Sch Informat & Control Engn, Fushun 113001, Peoples R China
基金
中国国家自然科学基金;
关键词
Injection molding process; Riccati equation; switched system; dwell time; ITERATIVE LEARNING CONTROL; MODEL-PREDICTIVE CONTROL; FAULT-TOLERANT CONTROL; H-INFINITY CONTROL; BATCH PROCESSES; SWITCHED SYSTEMS; DESIGN; CONVERGENCE; STABILITY; L(2)-GAIN;
D O I
10.1109/ACCESS.2019.2918020
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a limited rolling time domain-based hybrid tracking control method for injection and packing-holding phase in the injection molding process is proposed. A more flexible controller is designed by adding the adjustable weighting coefficient. First, the input and output models in different phases are established based on the collected input and output data, then, the appropriate state variables are selected to establish a multi-phase state space model. In addition, then, the above model is transformed into an extended state space model containing state variables and output tracking errors, which is transformed into a switched system model. Meanwhile, the performance indicators including the terminal state are selected for different phases, and the optimal hybrid control law is obtained by combining the Riccati equation and the boundary condition. In order to find the minimum run time of each phase for different phases, the dwell time method that depends on the Lyapunov function is designed. The method is simple in design and can improve production efficiency. Finally, the feasibility and effectiveness of the proposed method are verified by modeling and simulating the injection molding process and comparing with the traditional methods.
引用
收藏
页码:67446 / 67455
页数:10
相关论文
共 50 条
  • [1] HYBRID DYNAMIC OPTIMAL TRACKING CONTROL OF HYDRAULIC CYLINDER SPEED IN INJECTION MOLDING INDUSTRY PROCESS
    Ren, Zhigang
    Wu, Guoshen
    Wu, Zongze
    Xie, Shengli
    JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION, 2023, 19 (07) : 5209 - 5229
  • [2] A learning-based model predictive control scheme for injection speed tracking in injection molding process
    Ren, Zhigang
    Cai, Jianpu
    Zhang, Bo
    Wu, Zongze
    COMPLEX & INTELLIGENT SYSTEMS, 2024, : 7845 - 7861
  • [3] Online Control of the Injection Molding Process Based on Process Variables
    Michaeli, Walter
    Schreiber, Andreas
    ADVANCES IN POLYMER TECHNOLOGY, 2009, 28 (02) : 65 - 76
  • [4] Injection molding process control
    Speight, RG
    Thomas, AR
    ANTEC 2000: SOCIETY OF PLASTICS ENGINEERS TECHNICAL PAPERS, CONFERENCE PROCEEDINGS, VOLS I-III, 2000, : 3853 - 3857
  • [5] Domain-based Hybrid OpenFlow Network (HON)
    Bong, Zoebir
    Leong, Derrick Lim Teck
    Lee, Bu Sung
    2013 19TH IEEE INTERNATIONAL CONFERENCE ON NETWORKS (ICON), 2013,
  • [6] A Discrete Time Domain-Based MILP Framework for Control Parameter Tuning
    Arguello, Andres
    Rider, Marcos J.
    IEEE SYSTEMS JOURNAL, 2021, 15 (03): : 3462 - 3469
  • [7] Process control on injection molding machines
    Bozzelli, JW
    Cardinal, J
    INNOVATIONS IN PLASTICS IV - BASICS TO NEW TECHNOLOGIES: SPC PD3 REGIONAL TECHNICAL CONFERENCE (RETEC 96), 1996, : B1 - B4
  • [8] Control of the Injection Molding Process.
    Whisson, R.R.
    Plastvarlden, 1974, (01): : 22 - 25
  • [9] Online Simulation-Based Process Control for Injection Molding
    Johnston, Stephen P.
    Kazmer, David O.
    Gao, Robert X.
    POLYMER ENGINEERING AND SCIENCE, 2009, 49 (12): : 2482 - 2491
  • [10] Injection velocity control in filling process of injection molding
    Zhongguo Suliao/China Plastics, 2002, 16 (05):