• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.105-112
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• 2022

In this paper, unmanned underwater glider was designed for high-depth operation and adopted a bladder-type buoyancy controller for improving battery efficiency, and the motion controller controls the pitch angle by moving the internal mass battery. To improve the energy efficiency of the unmanned underwater glider, a layered PID controller that performs control by section was designed. Simulation program including 6-DOF motion equations and hydrodynamics coefficients of an unmanned underwater glider is constructed using Matlab/Simulink program. Control methods such as PID controller, sliding mode controller and layered PID controller were applied to the simulator to compare the dynamics performance and energy efficiency. As a result, the layered PID controller showed improved control performance compared to other controllers and improved energy efficiency of approximately 7.2% compared to PID controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.330-336
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• 2014

Many industrial processes such as continuous stirred tank reactors(CSTRs), desalination plant, distillation columns, pH neutralization processes and so on exhibit highly nonlinear characteristic and time-varying behavior during operation. The control of such processes has been challenging to control engineers. Hence, a variety of forms of PID controllers and their tuning rules for industrial processes have been developed to guarantee the best performance. In this paper, a scheme that designs the practical PID controller with an anti-windup strategy incorporating with an evolutionary algorithm(EA) is presented for the concentration control of a nonisothermal CSTR. EA is used to tune the parameters of the overall PID control process with anti-windup by minimizing the integral of absolute error(IAE). Simulation works for reference tracking and disturbance rejecting performances and robustness to parameter changes show the feasibility of using the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.279-284
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• 2014

This paper proposes a optimum design method for the Fuzzy PID controller of magnetic levitation-based Rail-Guided Vehicle(RGV). Since an attraction type levitation system is intrinsically unstable, it is difficult to completely satisfy the desired performance through the methods designed by conventional controllers. In the paper, the Fuzzy PID controller with fixed parameters are applied and then the optimum parameters of fuzzy PID controller are selected by genetic algorithm. For the fitness function of genetic algorithm, the performance index of PID controller is used. To verify the performance of the proposed method, we used Matlab/simulink model of Maglev and compared the proposed method with the performance of PID controller. The simulation results show that the proposed method is more effective than conventional PID controller.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.59-60
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• 2008

In this paper, we investigate the ability of the ARM processor to implement an industrial controller with or without embedded operating system. Discrete-time PID controllers are implemented and tested under various settings e.g. cache on/off, different clock frequencies using S3C2410X chip. A method of real-time application of discrete-time PID controller in WinCE environment is proposed. Based on the test result, we provide the maximum sampling frequencies of PID controller using ARM processor.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2268-2277
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• 2017

As constantly increasing wind power penetrates power grid, wind power plants (WPPs) are exerting a direct influence on the traditional power system. Most of WPPs are using variable speed constant frequency (VSCF) wind turbines equipped with doubly fed induction generators (DFIGs) due to their high efficiency over other wind turbine generators (WTGs). Therefore, the analysis of DFIG has attracted considerable attention. Precisely measuring optimum reference speed is basis of utilized maximum wind power in electric power generation. If the measurement of wind speed can be easily taken, the reference of rotation speed can be easily calculated by known system's parameters. However, considering the varying wind speed at different locations of blade, the turbulence and tower shadow also increase the difficulty of its measurement. The aim of this study is to design fuzzy controllers to replace the wind speedometer to track the optimum generator speed based on the errors of generator output power and rotation speed in varying wind speed. Besides, this paper proposes the fuzzy adaptive PID control to replace traditional PID control under rated wind speed in variable-pitch wind turbine, which can detect and analyze important aspects, such as unforeseeable conditions, parameters delay and interference in the control process, and conducts online optimal adjustment of PID parameters to fulfill the requirement of variable pitch control system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.3
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• pp.8-14
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• 2009

In this paper, it is proposed that the design of the PID controller with the internal model control structure for improved performance. Internal model was identification that is second-order plus dead time structure using final-value theorem and genetic algorithm The parameters of Controller are determined to minimize IAE(Integral of the Absolute value of the Error) and ITAE(Integral of the Time multiplied by the Absolute value of the Error) of performance index by internal model and numerical method. Simulation examples are given to show the better performance of the proposed method than conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.25-32
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• 2007

In this paper, a new method for first order plus dead time(FOPDT) model identification is proposed, which can identity multiple points on a process step response in terms of classification of time response. The process input and output to the test are decomposed into the transient part and the steady-state part. The steady-state part express one FOPDT model and the transient part express variously FOPDT model using least square estimation method. The optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.888-892
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• 2002

In this paper, parallel type fuzzy controller is designed by using a hybrid connected type fuzzy-PID controller and a model reference fuzzy controller. The first controller that consists a fuzzy-PI and a fuzzy-PD making a hybrid type fuzzy-PID controller plays a role as firstly reaching stable responses and secondly overcoming disturbance in plants. The second controller, model reference fuzzy controller, plays a role as reaching faster responses than other controllers. We have confirmed that we get rapid and stable responses and the controller overcomes disturbance in a short time when there happens disturbance by using parallel type fuzzy controller applying to DC motor in this paper.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.49-56
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• 2001

This paper presents a new approach to the problem based on neural network methods. Instead of using general controllers, neural networks PID control are used to control AC servo motor. The most popular and widely used control method in servo system control loops is PID type. PID controller has the features of simple structure, stability and reliability. But it has limitations in complex system control and can not remain above virtues under the conditions of parameters uncertain and environment uncertainties. AC servo motor controller is designed for drive of the cartesian coordinate type for machine tools.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1027-1037
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• 2017

Penetration of renewable energy sources makes the modern interconnected power systems to have more intelligence and flexibility in the control. Hence, it is essential to maintain the system frequency and tie-line power exchange at nominal values using Load Frequency Control (LFC) for efficient, economic and reliable operation of power systems. In this paper, intelligent tuning of the Proportional Integral Derivative (PID) controller for LFC in an interconnected power system is considered as a main objective. The chosen problem is formulated as an optimization problem and the optimal gain parameters of PID controllers are computed with three innovative swarm intelligent algorithms named Particle Swarm Optimization (PSO), Bacterial Foraging Optimization Algorithm (BFOA) and hybrid Bacterial Foraging Particle Swarm Optimization (BFPSO) and a comparative study is made between them. A new objective function designed with necessary time domain specifications using weighted sum approach is also offered in this report and compared with conventional objective functions. All the simulation results clearly reveal that, the hybrid BFPSO tuned PID controller with proposed objective function has better control performances over other optimization methodologies.