|
|
A new fuzzy self-tuning method for controlling packing pressure of a high-accuracy injection molding machine |
WANG Shuo1, YING Ji1, CHEN Zi-chen1, FENG Yu2 |
1. Zhejiang Province Key Laboratory of Advanced Manufacturing Technology, Institute of Modern Manufacturing Engineering, Zhejiang University, Hangzhou 310027, China; 2. Computational MultiPhysics Laboratory, Department of Mechanical Engineering, North Carolina State University, NC, 27695, USA |
|
|
Abstract According to the poor packing pressure control accuracy of the traditional injection molding machines, this paper presents a new injection system using servo motor-driving fixed pump which can provide different speed with the given injection process. The mathematical models were established based on non-Newtonian fluid dynamics for the hydraulic system and the viscous force of melted plastic between the barrel and screw. Based on the theoretical analysis, a new fuzzy selftuning(FST) method was proposed which combined the advantages of both the fuzzy control and the self-tuning control. The experimental data with packing pressure control showed that compared with the traditional PID algorithm, the FST algorithm has better performance with slighter overshooting, quicker response, shorter transient time and better control accuracy.
|
Published: 08 September 2011
|
|
精密注塑机保压压力的新型模糊自校正控制
针对传统注射成型装备中保压压力控制精度不高的问题,提出采用伺服电机驱动定量泵的复合系统.伺服电机配合注塑机不同工艺过程输出相应转速,提高控制性能,消除高压节流.建立注塑机注射过程的数学模型,分析料筒内螺杆所受熔融态塑料的黏性摩擦力,提出一种新型模糊自校正(FST)控制算法.该算法在模糊控制收敛迅速,鲁棒性强的特点基础上,结合自校正控制算法,提高系统的响应速度,降低注塑机保压过程中的压力超调,消除系统的滞后.通过与传统PID算法对比实验结果表明,该算法能够提高保压压力的响应速度和控制精度,从而达到精密注塑的要求.
|
|
[1] CHEN Z B, TURNG L S. A review of current developments in process and quality control for injection molding [J]. Advances in Polymer Technology, 2005, 24(3): 165-182. [2] TAN K K, TANG J C. Learningenhanced PI control of ram velocity in injection molding machines [J]. Engineering Applications of Artificial Intelligence, 2002, 15: 65-72. [3] YANG Y, GAO F R. Adaptive control of the filling velocity of thermoplastics injection molding [J]. Control Engineering Practice, 2000, 8: 1285-1296. [4] ZHENG D N, ALLEYNE A. Modeling and control of an electrohydraulic injection molding machine with smoothed filltopack transition [J]. Transactions of ASME, 2003, 125: 154-163. [5] RAFIZADEH M, PATTERSON W I, KAMAL M R. Physicallybased model of thermoplastics injection molding for control applications [J]. Int.Polymer Processing, (S0930777X), 1996, 11(4): 352-361. [6] CHEN Z B, TURNG L S. Adaptive online qulity control for injectionmolding by monitoring and controlling mold separation [J]. Polymer Engineering and Science, 2006, 10: 569-580. [7] ZHOU J, TURNG L S. Adaptive multiobjective optimization of process conditions for injection molding using a gaussian process approach [J]. Advances in Polymer Technology, 2007, 26(2): 71-85. [8] GAO Y H, TURNG L S, WANG X C. Adaptive geometry and process optimization for injection molding using the kriging surrogate model trained by numerical simulation [J]. Advances in Polymer Technology, 2008, 27(1): 1-16. [9] 应济,李长勇. 注塑机后模板顺序优化设计研究 [J]. 浙江大学学报:工学版,2006,40(6): 937-941. YING Ji,Li CHANGyong. Sequential optimization design research on rear mould board of injection machine [J]. Journal of Zhejiang University: Engineering Science, 2006,40(6): 937-941. [10] LIU T, GAO F R. Identification of integrating and unstable process from relay feedback [J]. Computers and Chemical Engineering, 2008, 32: 3038-3056. [11] SHI J, GAO F R, WU T J. Singlecycle and multicycle generalized 2D model predictive iterative learning control(2DGPILC) schemes for batch process [J]. Journal of Process Control, 2007, 17: 715-727. [12] 吴乐彬,王宣银,李强. 对接模拟并联六自由度平台的模糊免疫PID控制 [J]. 浙江大学学报:工学版,2008,42(3): 387-391. WU Lebin, WANG Xuanyin, LI Qiang. Fuzzyimmune PID control of a 6DOF parallel platform for docking simulation [J]. Journal of Zhejiang University: Engineering Science, 2008,42(3): 387-391. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|