HYBRID DYNAMIC OPTIMAL TRACKING CONTROL OF HYDRAULIC CYLINDER SPEED IN INJECTION MOLDING INDUSTRY PROCESS

被引:6
|
作者
Ren, Zhigang [1 ]
Wu, Guoshen [1 ]
Wu, Zongze [2 ,3 ]
Xie, Shengli [4 ]
机构
[1] Guangdong Univ Technol, Sch Automat, Guangdong HongKong Macao Joint Lab Smart Discrete, Guangzhou 510006, Peoples R China
[2] Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China
[3] Shenzhen Univ, Coll Mechatron & Control Engn, Shenzhen 518060, Peoples R China
[4] Guangdong Univ Technol, Sch Automat, Key Lab Intelligent Detect & Internet Things Mfg, Minist Educ, Guangzhou 510006, Peoples R China
基金
中国国家自然科学基金;
关键词
Industrial process; injection molding; optimal control; control parameterization; particle swarm optimization; PREDICTIVE CONTROL; SWITCHING TIME; OPTIMIZATION; VELOCITY; SYSTEM;
D O I
10.3934/jimo.2022169
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Injection speed control is one of the most essential components in the injection molding process. It is critical to implement fast and reliable injection speed optimization control for the effective manufacturing of injection molding products. In this paper, the speed tracking control problem of the hydraulic cylinder of an injection molding machine driven by a typical servo motor is studied. An efficient two-stage optimization framework that leverages the ideas of both control parameterization (CP) and particle swarm optimization (PSO) is proposed for generating the optimal signal input to achieve the required injection speed tracking over a certain time. To this end, the dynamic model of the hydraulic system in the injection molding equipment is firstly established and the optimal controller design problem is transformed into sequential optimal parameter decision problems, and the explicit expressions of the gradient information of the objective function as well as the constraint on the parameters of the decision variables are derived. Then, the PSO combined with the CP and gradient-based algorithm is utilized to to solve the parameters of the controller efficiently. The two-stage optimization framework proposed in this paper can improve the convergence speed of the CP method and the precision of the PSO and easy-to-implement in engineering and industrial deployment. Finally, the feasibility and effectiveness of the proposed design method are verified by experimental simulations.
引用
收藏
页码:5209 / 5229
页数:21
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