FPGA-Based Multiprocessor System for Injection Molding Control

Munoz-Barron, Benigno; Morales-Velazquez, Luis; Romero-Troncoso, René de Jesús; Rodriguez-Donate, Carlos; Trejo-Hernández, Miguel; Benítez-Rangel, Juan P.; Osornio-Ríos, Roque Alfredo

doi:10.3390/s121014068

Cited by 5 publications

(6 citation statements)

References 25 publications

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“…Apart from classical PID control, there are a variety of advanced control methods aimed to provide precise temperature management of the heaters with instable parameters. Precision temperature control can be obtained using advanced algorithms, such as an artificial neural network (ANN) [8][9][10], fuzzy-logic, or combined adaptive neuro fuzzy inference system (ANFIS) controller [11][12][13]. However, either classical or ANN-based controllers have to be tuned in the initial stage of operation.…”

Section: Of 13mentioning

confidence: 99%

An ANN-Based Temperature Controller for a Plastic Injection Moulding System

et al. 2019

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This paper proposes an approach to an ANN-based temperature controller design for a plastic injection moulding system. This design approach is applied to the development of a controller based on a combination of a classical ANN and integrator. The controller provides a fast temperature response and zero steady-state error for three typical heaters (bar, nozzle, and cartridge) for a plastic moulding system. The simulation results in Matlab Simulink software and in comparison to an industrial PID regulator have shown the advantages of the controller, such as significantly less overshoot and faster transient (compared to PID with autotuning) for all examined heaters. In order to verify the proposed approach, the designed ANN controller was implemented and tested using an experimental setup based on an STM32 board.

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Section: Of 13mentioning

confidence: 99%

An ANN-Based Temperature Controller for a Plastic Injection Moulding System

et al. 2019

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“…However, implementing a low-level code with a single task allows the processor to execute complex algorithms, optimizing computational capabilities. This work proposes to take advantage of the parallelism offered by the FPGA with the possibility of integrating a soft processor that executes a C or C++ code to execute low load and repetitive tasks [8] while freeing the processor for the execution of the algorithm without the operating system. The ECU uses the Zynq-7000 chip manufactured by Xilinx which also includes a dual-core Advanced RISC (reduced instruction set computer) Machine (ARM) processor [9].…”

Section: Introductionmentioning

confidence: 99%

Low-Cost FPGA-Based Electronic Control Unit for Vehicle Control Systems

Fernández

Vargas

García

et al. 2019

Sensors

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The development of new control algorithms in vehicles requires high economic resources, mainly due to the use of generic real-time instrumentation and control systems. In this work, we proposed a low-cost electronic control unit (ECU) that could be used for both development and implementation. The proposed electronic system used a hybrid system on chip (SoC) between a field-programmable gate array (FPGA) and an Advanced RISC (reduced instruction set computer) Machine (ARM) processor that allowed the execution of parallel tasks, fulfilling the real-time requirements that vehicle controls demand. Another feature of the proposed electronic system was the recording of measured data, allowing the performance of the implemented algorithm to be evaluated. All this was achieved by using modular programming that, without the need for a real-time operating system, executed the different tasks to be performed, exploiting the parallelism offered by the FPGA as well as the dual core of the ARM processor. This methodology facilitates the transition between the designing, testing, and implementation stages in the vehicle. In addition, our system is programmed with a single binary file that integrates the code of all processors as well as the hardware description of the FPGA, which speeds up the updating process. In order to validate and demonstrate the performance of the proposed electronic system as a tool for the development and implementation of control algorithms in vehicles, a series of tests was carried out on a test bench. Different traction control system (TCS) algorithms were implemented and the results were compared.

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“…This increases the complexity of the DSP control architecture along with the computational load because the parameters have to be controlled in parallel. [2] A different situation occurs when the set-point temperature is different from the balanced temperature. [17] The further the set-point temperature is from the balanced temperature, the further the PID constants are from their optimum values.…”

Section: Digital Pid Control Systemmentioning

confidence: 99%

“…[2,5] These parameters that determine the final product quality in most cases are correlated with one another, and therefore, this correlation makes it difficult to control them accurately.…”

Section: Heating and Cooling Injection Molding Systemmentioning

confidence: 99%

“…[1] The plastic injection molding (PIM) process is generally carried out by heating the plastic, transporting the polymer into the mold, cooling the mold, and finally ejecting the product. [2] The closed and empty mold is prepared for melting the plastic charged in the injection unit. The melted polymer is injected through the mold cavities with the screw, and then the injection pressure is kept constant to prevent changes in dimensions of the piece.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimized Digital Proportional Integral Derivative Controller for Heating and Cooling Injection Molding System

Jeong¹,

Kim²,

Lee³

2015

Journal of Electrical Engineering and Technology

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-Proportional integral derivative (PID) control is one of the conventional control strategies.Industrial PID control has many options, tools, and parameters for dealing with the wide spectrum of difficulties and opportunities in manufacturing plants. It has a simple control structure that is easy to understand and relatively easy to tune. Injection mold is warming up to the idea of cycling the tool surface temperature during the molding cycle rather than keeping it constant. This "heating and cooling" process has rapidly gained popularity abroad. However, it has discovered that raising the mold wall temperature above the resin's glass-transition or crystalline melting temperature during the filling stage is followed by rapid cooling and improved product performance in applications from automotive to packaging to optics. In previous studies, optimization methods were mainly selected on the basis of the subjective experience. Appropriate techniques are necessary to optimize the cooling channels for the injection mold. In this study, a digital signal processor (DSP)-based PID control system is applied to injection molding machines. The main aim of this study is to optimize the control of the proposed structure, including a digital PID control method with a DSP chip in the injection molding machine.

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FPGA-Based Multiprocessor System for Injection Molding Control

Cited by 5 publications

References 25 publications

An ANN-Based Temperature Controller for a Plastic Injection Moulding System

An ANN-Based Temperature Controller for a Plastic Injection Moulding System

Low-Cost FPGA-Based Electronic Control Unit for Vehicle Control Systems

Optimized Digital Proportional Integral Derivative Controller for Heating and Cooling Injection Molding System

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