• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1777-1782
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• 2011

Brushless DC motors applied in many control systems because of the good respose characteristic and the easy control characteristic. The speed control of the BLDC motors is important in the systems. This paper has designed PSO-PID speed controller for the speed control of BLDC motors. The PSO algorithm optimized the parameters of the PID controller in the PSO-PID speed controller. The several methods obtained the optimal inertia weight of the PSO algorithm by comparison. The optimal inertia weight of the PSO algorithm optimized the PSO-PID speed controller for BLDC motors. This paper confirmed the performance of proposed PSO-PID speed controller through simulation results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.330-338
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• 2018

The proportional-integral-derivative(PID) controller has been widely used in the industry because of its robust performance and simple structure in a wide range of operating conditions. However, the AVR(Automatic Voltage Regulator) as a control system is not robust to variations of the power system parameters. Therefore, it is necessary to use PID controller to increase the stability and performance of the AVR system. In this paper, a novel design method for determining the optimal PID controller parameters of an AVR system using the particle swarm optimization(PSO) algorithm is presented. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. In order to assist estimating the performance of the proposed PSO-PID controller, a new performance criterion function is also defined. This evaluation function is intended to reflect when the maximum percentage overshoot, the settling time are given as design specifications. The ITAE evaluation function should impose a penalty if the design specifications are violated, so that the PSO algorithm satisfies the specifications when searching for the PID controller parameter. Finally, through the computer simulations, the proposed PSO-PID controller not only satisfies the given design specifications for the terminal voltage step response, but also shows better control performance than other similar recent studies.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.59-64
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• 2022

Vibration is one of the factors that degrades the performance of equipment and measurement equipment used in high-tech industries such as semiconductors and display. The vibration isolator is classified into passive type and active type. The passive vibration isolator has the weakness of insufficient vibration isolation performance in the low frequency band, so an active vibration control system that can overcome these problems is used recently. In this paper, PID controller is used to control the active vibration isolator. Methods for setting the gain of the PID controller include the Zeigler-Nichols method, the pole placement method. These methods have the disadvantage of requiring a lot of time or knowing the system model accurately. This paper proposes the gain auto tuning method of the active vibration isolator applied with the PSO algorithm, which is an optimization algorithm that is easy to implement and has stable convergence performance with low calculations. It is expected that it will be possible to improve vibration isolation performance and reduce the time required for gain tuning by applying the proposed PSO algorithm to the active vibration isolator.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.490-498
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• 2016

Proportional Integral Derivative (PID) controller tuning is an area of interest for researchers in many areas of science and engineering. This paper presents a new algorithm for PID controller tuning based on a combination of bacteria foraging and particle swarm optimization. BFO algorithm has recently emerged as a very powerful technique for real parameter optimization. To overcome delay in an optimization, combine the features of BFOA and PSO for tuning the PID controller. This new algorithm is proposed to combine both the algorithms to get better optimization values. The real time prototype model of paper machine is designed and controlled by using PIC microcontroller embedded with the programming in C language.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1380-1385
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• 2004

In this paper, auto-tuning technique of the PID controller gain by particle swarm optimization algorithm is presented. PID controller is easy to implement to numerous control systems. After PID gain tuning is completed, its result could be implemented to control spacecraft vibration such as jitter that is high frequency vibration usually over 10Hz. The off-line PID controller tuning is done under system nonlinearities and uncertainties existence, then its result is applied to control experiment device to prove the PSO efficiencies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.185-188
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• 2009

In this paper, Position Controller for balance of Seesaw System design using PID Algorithm. Seesaw System is that it's system use widely to analyze of ship or flight dynamics, Inverted Pendulumand, Robot System, manage system for theory of modern control system and all sorts of analysis. In case of Seesaw System, it's necessity that understand and analysis of system and correct selection of parameter because the system is strong nonlinear control system. It guarantees efficiency and stability to adapt quickly for disturbance or change of controller from PID Algorithm of guarantee safe from simple and long history and PSO(Particle Swarm Optimization) that sort of metaheuristic optimization that need to accuracy and fast PID parameter tuning.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.877-885
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• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2556-2563
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• 2021

Metaheuristic algorithms can work well in solving or optimizing problems, especially those that require approximation or do not have a good analytical solution. Particle swarm optimization (PSO) is one of these algorithms. The response quality of these algorithms depends on the objective function and its regulated parameters. The nonlinear nature of the pressurized light-water nuclear reactor (PWR) dynamics is a significant target for PSO. The two-point kinetics model of this type of reactor is used because of fission products properties. The proportional-integral-derivative (PID) controller is intended to control the power level of the PWR at a short-time transient. The absolute error (IAE), integral of square error (ISE), integral of time-absolute error (ITAE), and integral of time-square error (ITSE) objective functions have been used as performance indexes to tune the PID gains with PSO. The optimization results with each of them are evaluated with the number of function evaluations (NFE). All performance indexes achieve good results with differences in the rate of over/under-shoot or convergence rate of the cost function, in the desired time domain.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1297-1302
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• 2014

This paper presents modern optimization methods for determining the optimal parameters of proportional-integral-derivative (PID) controller for coupled tank systems. The main objective is to obtain a fast and stable control system for coupled tank systems by tuning of the PID controller using the Particle Swarm Optimization algorithm. The result is compared in terms of system transient characteristics in time domain. The obtained results using the Particle Swarm Optimization algorithm are also compared to conventional PID tuning method like the Ziegler-Nichols tuning method, the Cohen-Coon method and IMC (Internal Model Control). The simulation results have been simulated by MATLAB and show that tuning the PID controller using the Particle Swarm Optimization (PSO) algorithm provides a fast and stable control system with low overshoot, fast rise time and settling time.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.22-34
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• 2006

o GA-BF approach for improvement of learning and optimization in GA o GA-BF has better response on various test functions o Satisfactory PID controller tuning in AVR, motor vector control systems o Potentially useful in many practically important engineering optimization problems