• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4A
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• pp.337-342
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• 2010

Generally most sluice gates are closed and opened by a mechanical winch, a winch using an oil-pressure, or a winch mixing both. Because of their size and structure, they should be safely operated with more than two pulling devices helping each other. At the moment of their opening and closing, there usually occur some additional loads to the structure which cannot be exactly measurable at the stage of designing. Such additional loads can cause the sluice gate to be unbalanced and make it hard to open and close the gate, and by also overloading a winch, they can inflict a significant damage to the safety of the sluice gate. This paper explains a FDC(Force-Displacement Control) system which simultaneously considered the oil-pressure and displacement in order to evenly distribute the force and make a winch balanced at the opening and closing motion. This FDC system was implemented by means of the PID(Proportional Integral Derivative) function of XG 5000 program. It was experimented on a model of the sluice gate winch with the hydraulic oil pressure cylinder. The experiments showed that the developed FDC system made the winch of hydraulic oil pressure cylinder open and close cooperatively in spite of various external loads. Therefore the FDC system is proven effective when it is applied to a winch of sluice gate.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2609-2614
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• 2011

A proportional integral derivative (PID) controller is designed and applied to a magnetic levitation conveyor system to control the levitation gap length of the electromagnet constantly. The PID gain parameters are optimized by response surface methods (RSM). The controller is verified with the state-space model of electromagnetic suspension by MATLAB/SIMULINK program. And, the controller and the state-space model are also verified experimentally. Simulation and experimental results shows the effectiveness of the PID gain tuning by RSM as compared with the classical PID tuning.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.12
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• pp.57-64
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• 2007

There have been many researches for optimal controllers in multivariable systems, and they generally use accurate linear models of the plant dynamics. Real systems, however, contain nonlinearities and high-order dynamics that may be difficult to model using conventional techniques. Therefore, it is necessary a PID gain tuning method without explicit modeling for the multivariable plant dynamics. The PID tuning method utilizes the sign of Jacobian and gradient descent techniques to iteratively reduce the error-related objective function. This paper, especially, focuses on the role of I-controller when there is a steady state error. However, it is not easy to tune I-gain unlike P- and D-gain because I-controller is mainly operated in the steady state. Simulations for an overhead crane system with dynamic friction show that the proposed PID-LC algorithm improves controller performance, even in the steady state error.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1869-1875
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• 2008

Recently, a direct data-driven synthesis of a proportional integral derivative(PID) controller for a linear time-invariant(LTI) plant was presented in [1]. The authors showed that a complete set of PID controllers achieving robust performance and stability can be calculated directly from frequency response(FR) data without an identified transfer function model. However, it is not convenient to use this method because it requires complicated numerical algorithms to find specific frequencies which are solutions of an identical equation. The method also requires determination of the boundary of the controller's parameters from a finite set of FR data. In this paper, we present the development of a user-friendly Matlab toolbox based on the method in [1]. This toolbox allows us to obtain a complete three-dimensional(3-D) graphical solution of PID controllers that meet multiple design objectives. Several examples are given to demonstrate the use of the toolbox.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.72-81
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• 2000

In this paper, we design an adaptive neuro-fuzzy inference system(ANFIS) precompensator for load frequency control of 2-area power systems. While proportional integral derivative (PID) controllers are used in power systems, they may have some problems because of high nonlinearities of the power systems. So, a neuro-fuzzy-based precompensation scheme is incorporated with a convectional PID controller to obtain robustness to the nonlinearities. The proposed precompensation technique can be easily implemented by adding a precompensator to an existing PID controller. The applied neruo-fuzzy inference system precompensator uses a hybrid learning algorithm. This algorithm is to use both a gradient descent method to optimize the premise parameters and a least squares method to solve for the consequent parameters. Simulation results show that the proposed control technique is superior to a conventional Ziegler-Nichols PID controller in dynamic responses about load disturbances.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.212-218
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• 2021

The Proportional Integral Derivative (PID) controller is the most popular industrial controller and more than 90% process industries use this controller. During the past 50 years, numerous good tuning methods have been proposed for Single Input Single Output Systems. However, design of PI/PID controllers for multivariable processes is a challenge for the researchers. A comparative study of three PID controllers design methods has been carried-out. These methods include the DS (Direct Synthesis) method, IMC (Internal model Control) method and ETF (Effective Transfer Function) method. MIMO PID controllers are designed for a number of 2×2, 3×3 and 4×4 process models with multiple delays. The performance of the three methods has been evaluated through simulation studies in Matlab/Simulink environment. After extensive simulation studies, it is found that the Effective Transfer Function (ETF) Method produces better output responses among two methods. In this work, only decentralized methods of PID controllers have been studied and investigated.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.11-18
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• 2021

The Proportional Integral Derivative (PID) controller is the most popular industrial controller and more than 90% process industries use this controller. During the past 50 years, numerous good tuning methods have been proposed for Single Input Single Output Systems. However, design of PI/PID controllers for multivariable processes is a challenge for the researchers. A comparative study of three PID controllers design methods has been carried-out. These methods include the DS (Direct Synthesis) method, IMC (Internal model Control) method and ETF (Effective Transfer Function) method. MIMO PID controllers are designed for a number of 2×2, 3×3 and 4×4 process models with multiple delays. The performance of the three methods has been evaluated through simulation studies in Matlab/Simulink environment. After extensive simulation studies, it is found that the Effective Transfer Function (ETF) Method produces better output responses among two methods. In this work, only decentralized methods of PID controllers have been studied and investigated.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.627-630
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• 2004

The PID type controller has been widely used in industrial application due to its simply control structure, ease of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller (fuzzy P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid fuzzy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.