Self-tuning Scheme Fuzzy PID Based Barrel Temperature Controller For Plastic Injection Molding Machine

Plastic Injection molding is a manufacturing process that obtains the appropriate shape and size of the plastic materials by using the process of molding.By the manufacturing method,the molten plastic material is passed into the die of the appropriate shape,corresponding to the shape of the product we designed,then we can allow solidifying until it solidifies and gets its shape.Plastic manufacturing is ideal for manufacturing a large amount of identical objects.Main Advantages of plastic molding manufacturing are repeatable large tolerances,high manufacturing,low labor cost,plenty of materials to be used,and minimum material losses.In this manufacturing process,the material is passed through different heating zones to heat by a heater.Then the plastic material will become below the softening point and then injected into the molding to produce different plastic materials.Thus,in the plastic manufacturing process,temperature control of the Injection molding machine is a critical and important task.This study deals with the barrel temperature control of Plastic Injection molding.The barrel temperature of the plastic Injection machine is controlled to the appropriate temperature range.In the plastic manufacturing process,the most used controller for barrel temperature control is PID and PI controllers.Since an electric heaters are time-varying processes and nonlinear,by applying PID controllers is not easy to meet the exact control requirement.Because have not a good dynamic response,they are not robust and record large overshoot.So,under this study,the fuzzy controller which nonlinear and fault-tolerant controller is applied to improve the PID controller and succeed better results on transient and steady-state requirements.Therefore,under this study,the model of the barrel temperature heater is analyzed by using SIMULINK/MATLAB and then a self-tuning scheme fuzzy PID based controller has been simulated and designed,and its efficiency has been compared with traditional PID controller and Fuzzy logic controller.The efficiency of the controllers is analyzed in terms of steady-state and transient performance and tested by feed zone,transition zone,and metering zone of the Plastic Injection molding machine.The PID controller model was applied by using PID tuning techniques like the Ziegler Nichols Tuning algorithm,Cohen-Coon Tuning algorithm.Integral of time-weighted absolute error Tuning algorithm,and PID extension tool by using MATLAB software.From those,MATLAB PID extension tool Tuning algorithm is achieved a better result by small overshoot from the other PID tuning mechanism and applied this tuning algorithm for Barrel temperature control of plastic Injection molding machine.For fuzzy logic controller prepared seven linguistic variables and 49 IF-THEN rules of fuzzy Inference,and finally,on fuzzy PID controller apply 147 IF-THEN statements of fuzzy Inference system.So,49 IF-THEN statements for KP,49 IF-THEN statements for KI.and 49 IF-THEN statements for KD.The efficiency of the proposed model fuzzy PID,Fuzzy logic controller,and PID controller is approved by simulation analysis using MATLAB/SIMULINK.The feed zone is operated by 90℃ and it is recorded by the simulation outputs the overshoot is 14.68%.rising time 15.1 63 seconds,settling time 120 seconds,pick time 30 seconds,with Less oscillatory,and without steady-state error is achieved by PID controller.Also,the fuzzy logic controller achieves with no overshoot,rising time 21.187 seconds,settling time 90 seconds,with no pick time,without oscillatory,and steady-state error 5.2.In addition,the fuzzy PID controller achieves with no overshoot,rising time 21.013 seconds,settling time 70 seconds,with no pick time,without oscillatory,and without steady-state error.The Transition zone is operated by 210℃ and it is recorded by the simulation outputs the overshoot is 25.949%,rising time 14.709 seconds,by settling time 115 seconds,pick time 30 seconds,with Less oscillatory,and without steady-state error is achieved by PID controller.Also,the fuzzy logic controller achieves with no overshoot,rising time 10.513 seconds,settling time 60 seconds,with no pick time,without oscillatory,and steady-state error 5.02.In addition,the fuzzy PID controller achieves with no overshoot,rising time 9.299 seconds,settling time 55 seconds,with no pick time,without oscillatory,and without steady-state error.The Metering zone is operated by 240℃ and it is recorded by the simulation outputs the overshoot is 25.949%,rising time 14.491 seconds,by settling time 110 seconds,pick time 30 seconds,with Less oscillatory,and without steady-state error is achieved by PID controller.Also,the fuzzy logic controller achieves with no overshoot,rising time 9.553 seconds,settling time 55 seconds,with no pick time,without oscillatory,and steady-state error 4.2.In addition,the fuzzy PID controller achieves with no overshoot,rising time 8.088 seconds,settling time 52 seconds,with no pick time,without oscillatory,and without steady-state error.The fuzzy PID controller can improve the barrel temperature of a plastic Injection molding machine within tolerable limits despite parameter variations like settling time,pick time,rising time,pick overshoot,and steady-state error.Therefore depending on the simulation output of the feed zone,transition zone,and metering zone the proposed fuzzy PID controller has achieved a more satisfactory result than PID controller and Fuzzy logic.