System Modeling and Analysis for Injection Molding Machine Take-Out Manipulator

2011 ◽  
Vol 55-57 ◽  
pp. 587-590
Author(s):  
Chi Wu Bu
Keyword(s):  
Injection Molding ◽  
Simulation Model ◽  
Trajectory Tracking ◽  
Structural Design ◽  
Dynamic Models ◽  
System Modeling ◽  
Control Torque ◽  
Molding Machine ◽  
Modeling And Analysis ◽  
And Control

A 4-DOF joint type manipulator is presented for injection molding machines. The kinematic and dynamic models of the manipulator have been built. The simulation model has been finished by MATLAB/Simulink/SimMechanics. Results show the property of the trajectory tracking and control torque of the manipulator. It can provide basis for the structural design for take-out manipulators of injection molding machines.

Design and Motion Simulation of the Clamping Mechanism of Micro-Structure Injection Molding Machine

2014 ◽  
Vol 945-949 ◽  
pp. 670-675 ◽  
Author(s):  
Bai Ge Chou ◽  
Heng Zhi Cai ◽  
Gang Zhou ◽  
Ya Jun Zhang ◽  
Jian Zhuang
Keyword(s):  
Injection Molding ◽  
Kinetic Characteristic ◽  
Clamping Force ◽  
Molding Machine ◽  
Micro Structure ◽  
Injection Molding Machine ◽  
Micron Size ◽  
Lqr Controller ◽  
And Control ◽  
Micro Structures

Micro-structure injection molding machine is mainly used for processing the plastic products in micron-size or with micro-structures. This paper focuses on the design and control of the clamping mechanism of micro-structure injection molding machine. Firstly, the deformation of the clamping mechanism was analyzed. The simulation results shows that the clamping force is 5.0051×105N, and it’s bigger than the design value 500kN. Secondly, the kinetic characteristic of the clamping was simulated by ADAMS software. The curves of the displacement, velocity, clamping force of moving platen were analyzed. Thirdly, the control model of clamping mechanism was established. And the LQR controller was designed and simulated by Matlab. The rise time is 0.010s, the settling time is 0.026s and the steady-state is 0.307m.

scholarly journals Design of Multimodel based MPC and IMC control schemes applied to injection molding machine

2014 ◽  
Vol 3 (2) ◽  
pp. 82
Author(s):  
Kanaga Lakshmi ◽  
D. Manamalli ◽  
M. Mohamed Rafiq
Keyword(s):  
Injection Molding ◽  
Temperature Control ◽  
Weighted Average ◽  
Injection Molding Process ◽  
Monitoring And Control ◽  
Molding Machine ◽  
Molding Process ◽  
Melt Temperature ◽  
Injection Molding Machine ◽  
And Control

Good control of plastic melt temperature for injection molding is very important in reducing operator setup time, ensuring product quality, and preventing thermal degradation of the melt. The controllability and set points of barrel temperature also depend on the precise monitoring and control of plastic melt temperature. Motivated by the practical temperature control of injection molding, this paper proposes MPC and IMC based control scheme. A robust system identification and control methodology is developed which uses canonical varieties analysis for identification and model predictive control for regulation. The injection molding process consists of three zones and the mathematical model for each of the zone is different. The control output for each zone controller is assigned a weight based on the computed probability of each model and the resulting action is the weighted average of the control moves of the individual zone controllers. Keywords: Injection-Molding Machine (IMM), IMC Control, Temperature Control.

Loading system and control strategy for simulating wind turbine loads

2015 ◽  
Vol 23 (11) ◽  
pp. 1739-1752 ◽  
Author(s):  
Xiu-xing Yin ◽  
Yong-gang Lin ◽  
Wei Li ◽  
Hang-ye Ye
Keyword(s):  
Wind Turbine ◽  
Control Strategy ◽  
Reference Frames ◽  
System Modeling ◽  
Axial Loading ◽  
Degree Of Freedom ◽  
Rotating Disc ◽  
Modeling And Analysis ◽  
Loading System ◽  
And Control

A novel loading control system is proposed to accurately simulate the five-degree-of-freedom loads experienced by a real wind turbine. For this system, the real wind rotor and blades are replaced by an equivalent rotating disc and driven by an electric motor. A set of loading actuators are uniformly placed around this disc and are regulated to accurately create these turbine loads. In this paper, the five-degree-of-freedom turbine loads are defined in blade and hub reference frames. A load-decomposition based loading control strategy is presented to decompose such loads into reference loading forces for each actuator. An axial loading actuator is used for system modeling and analysis. Experimental results have validated that the proposed loading system and control strategy can accurately simulate the representative turbine loads with a good confidence level.

Modeling and Control of an Electro-hydraulic Injection Molding Machine With Smoothed Fill-to-Pack Transition*

2003 ◽  
Vol 125 (1) ◽  
pp. 154-163 ◽  
Author(s):  
Danian Zheng ◽  
Andrew Alleyne
Keyword(s):  
Injection Molding ◽  
Process Model ◽  
Flow Characteristics ◽  
Hydraulic Actuator ◽  
Molding Machine ◽  
Transfer Scheme ◽  
Injection Molding Machine ◽  
Modeling And Control ◽  
And Control ◽  
Injection Cycle

In this paper the modeling of a typical injection cycle for an injection-molding machine (IMM) is examined. Both the mold filling and mold packing phases of the cycle are examined along with a critical fill-to-pack transition. The novelty in this modeling work is that the nonlinear model considers both the machine hydraulic actuator and polymer flow characteristics in extensive detail. The simulation model is validated against experimental data and demonstrates the availability of a relatively accurate system model for full cycle control design of this electro-hydraulic system. The accurate process model is used in the design of a controller for the injection cycle including the fill-to-pack transition. The overall algorithm includes two Iterative Learning Controllers connected by a bumpless transfer scheme between them. The algorithm is successfully tested through model simulations and machine experiments. The simulation and experimental results presented demonstrate a significantly smoother control signal and pressure transient between the two learning controlled phases as well as overall tracking convergence for each phase.

Schematic Design and Research on Steering Mechanism of Drilling Robot

2012 ◽  
Vol 189 ◽  
pp. 321-325 ◽  
Author(s):  
Xiao Gang Jian ◽  
Ye Feng Wang ◽  
Peng Chun Yang
Keyword(s):  
Structural Design ◽  
Rotation Axis ◽  
Body Parts ◽  
Modeling And Analysis ◽  
Kinematics Simulation ◽  
Steering Mechanism ◽  
Turning Radius ◽  
And Control ◽  
Steering Methods ◽  
Peak Value

Through the research on drilling robot at home and abroad, this paper divides steering methods into two types: steering caused by radial motion of body parts; steering caused by deflection of the head. Based on this classification, several schematic designs of steering mechanism are proposed. Respectively, structural design and principle analysis of steering mechanisms are carried out. And steering mechanism 3 is chosen the best one through comparison from the following aspects: No. of motors in the steering mechanism, size, turning radius and control difficulty. In order to prove its feasibility theoretically, the detailed modeling and analysis are presented. The results of DOF (degree of freedom) calculation and kinematics simulation of the head point show that its motion is determined and no collision exists between the parts during the kinematical process. The relation among peak value of rollers’ trajectory H, distances from rollers to the rotation axis of the cylindrical cam r and maximum deflection angle θmax is analyzed by building the deflection model, which lays foundation for further optimization.

scholarly journals Hybrid Systems Modeling for (Cancer) Systems Biology

2015 ◽  
Author(s):  
Roel I.J. Dobbe ◽  
Claire J. Tomlin
Keyword(s):  
Hybrid Systems ◽  
Dynamic Models ◽  
Complex Dynamics ◽  
System Modeling ◽  
Biological Data ◽  
Systems Modeling ◽  
Modeling And Analysis ◽  
Space And Time ◽  
Cancer Systems Biology ◽  
Gene Switching

The advent of biological data of increasingly higher resolution in space and time has triggered the use of dynamic models to explain and predict the evolution of biological systems over space and time. Computer-aided system modeling and analysis in biology has led to many new discoveries and explanations that would otherwise be intractable to articulate without the available data and computing power. Nevertheless, the complexity in biology still challenges many labs in capturing studied phenomena in models that are tractable and simple enough to analyze. Moreover, the popular use of ordinary differential equation models have their limitations in that they solely capture continuous dynamics, while we observe many discrete dynamic phenomena in biology such as gene switching or mutations. Hybrid systems modeling provides a framework in which both continuous and discrete dynamics can be simulated and analyzed. Moreover, it provides techniques to develop approximations and abstractions of complex dynamics that are tractable to analyze.

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