• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1383-1388
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• 2015

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.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2301-2309
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• 2018

In a field-oriented vector-controlled permanent magnet synchronous motor (PMSM) control system, the d-axis current control loop can offer a free degree of freedom which can be used to improve control performances. However, in the industry the desired d-axis current command is usually set as zero without using the free degree of freedom. This paper proposes a method to use the degree of freedom for control performance improvement. It is assumed that both the inner loop proportional-integral (PI) current controller and the q-axis outer loop PI speed controller are tuned by the well-known tuning rules. This paper gives an optimal d-axis reference current command generator such that some useful performance indexes are minimized and/or a tradeoff between conflicting performance criteria is made. This paper uses a differential evolution algorithm to autotune the parameter values of the optimal d-axis reference current command generator. This paper implements the proposed control system in real time on a Texas Instruments TMS320F28335 floating-point DSP. This paper also gives experimental results showing the practicality and feasibility of the proposed control system, along with simulation results.

• Proceedings of the KIEE Conference
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• 2008.04c
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• pp.128-130
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• 2008

This paper presents an algorithm to design a self-tuning proportional-integral(PI) speed controller for servo systems. The control gains are calculated with estimated system parameters, i.e. inertia and viscous damping which are estimated by initial operation. The simulation and experimental results show the feasibility and performance of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.959-962
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• 2010

There are a lot of methods available in designing PID(Proportional-Integral-Derivative) and Lead/Lag controllers in the industrial field of technology because of their useful advantages such as simplicity and robustness. In an early stage of development process, a computational simulation approach is a very efficient tool for the designs of the controllers. Thus, in this paper we propose a cost-effective, and practically efficient. The PID and Lead/Lag controllers. To show the effectiveness of the proposed Lead/Lag controller, we compare and contrast of the simulation results of each controller with the Matlab simulator. Although we have only considered the DC motors for the controllers, but it could be extended in future developments to more complex plants. As a result, the proposed frameworks could be used to solve industrial problems such as a reduction in development cycle time and minimizing system errors.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.86-86
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• 2000

This paper describes a neural network based fuzzy type PID control scheme. The PID controller is being widely used in industrial applications. however, it is difficult to determine the appropriate PID gains for (he nonlinear system control. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based fuzzy type PID controller whose scaling factors were adjusted automatically. The value of initial scaling factors of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods and then they were adjusted by using neural network control techniques. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The result of practical experiment on the magnetic levitation system, which is known to be hard nonlinear, showed the proposed controller's excellent performance.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.22-30
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• 2001

This paper describes a neural network based fuzzy PID control scheme. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriated PID gains in nonlinear systems and systems with long time delay and so on. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based self tuning fuzzy PID controller of which output gains were adjusted automatically. The tuning parameters of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods. Then they were adjusted by using proposed neural network learning algorithm. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The experiment on the magnetic levitation system, which is known to be heavily nonlinear, showed the proposed controller's excellent performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.797-803
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• 2012

Proportional solenoid valves are a modulating type that can control the displacement of valves continuously by means of electromagnetic forces proportional to the solenoid coil current. Because the solenoid-type modulating valves have the advantages of fast response and compact design over air-operated or motor-operated valves, they have been gaining acceptance in chemical and power plants to control the flow of fluids such as water, steam, and gas. This paper deals with the auto tuning of the position controller that can provide the proportional and integral gain automatically based on the dynamic system identification. The process characteristics of the solenoid valve are estimated with critical gain and critical period at a stability limit based on implemented relay feedback, and the controller parameters are determined by the classical Ziegler-Nichols design method. The auto-tuning algorithm was verified with experiments, and the effects of the operating point at which the relay control is activated as well as the relay amplitude were investigated.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1262-1264
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• 2003

The author Present a modified multiloop algorithm including feedforward for controlling a 45kW step down chopper in the power supply of Maglev. The control law for the duty cycle consists of three terms. The first is the feedforward term which compensates for variations in the input voltage. The second term consists of the difference between the slowly moving inductor current and output current. The third term consists of proportional and integral terms involving the perturbation in the output voltage. This perturvation is derived by subtracting the desired output voltage from the actual output voltage. The proportional and integral action stabilizes the system and minimizes output voltage error. To verify the validity of the proposed multiloop controller, simulation study was tried using Matlab/sirnulink.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.480-487
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• 1999

In this paper we propose a neural network precompensated PID(NNP PID) controller for load frequency control of 2-area power system. While proportional integral derivative(PID) controllers are used in power system they have many problems because of high nonlinearities of the power system So a neural network-based precompensation scheme is adopted into a conventional PID controller to obtain a robust control to the nonlinearities. The applied neural network precompen-sator uses an error back-propagation learning algorithm having error and change of error as inputand considers the changing component of forward term of weighting factor for reducing of learning time. Simulation results show that the proposed control technique is superior to a conventional PID controller and an optimal controller in dynamic responses about load disturbances. The pro-posed technique can be easily implemented by adding a neural network precompensator to an existing PID controller.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.3
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• pp.139-143
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• 1999

This paper is on realization of the speed-sensorless vector control of an induction motor using the RLS(Recursive Least Square) algorithm. The speed estimator is including the RLS algorithm and a rotor flux observer. The RLS algorithm has speed and rotor time constant as parameter vectors and rotor flux observer is designed to have robustness to stator resistance variation and through the IP(Integral and Proportional) speed controller stable performance is obtained for estimating rotor speed. Finally the total algorithm are realized in induction motor drive system and its effectiveness is verified.