• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.69-69
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• 2000

Control systems using a hydraulic cylinder as an actuator are modeled to a nonlinear system owing to varying of moments and nonlinearities of hydraulic itself. In this paper, we want to control nonlinear hydraulic systems by adopting the fuzzy PID control technique which include nonlinear time varying control parameters. To do this, we propose the design method of fuzzy Pm controller and in order to assure effectiveness of fuzzy PID controller, computer simulations were executed for the control system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.2
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• pp.62-69
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• 2000

In this paper, we design a GA-fuzzy precompensated PID controller for the load frequency control of two-area interconnected power system. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic-based precompensation approach for PID controller. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PID controller. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional PID control and a fuzzy precompensated PID control in dynamic responses about the load disturbances of power system and is convinced robustness reliableness in view of structure.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.139-147
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• 1996

PID control has been widely used for real control systems. Particularly, there are many researches on control schemes of tuning PID gains. However, to the best of our knowledge, there is no result for discrete-time systems with unknown time-delay and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown papameters and unknown time-delay system. A numerical simulation was presented to illustrate the effectiveness of this method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.9
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• pp.810-817
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• 2001

Performance of a water-to-water multi-type heat pump system using R22 which has tow indoor units has been investigated experimentally. The refrigerant flow rate of each indoor unit was regulated by an electronic expansion valve and the total refrigerant flow rate of the system was controlled by a variable speed compressor. In the system, evaporator outlet pressure of refrigerant and outlet temperatures of secondary fluid from indoor units were selected as control variables. Experiments were executed for both cooling and heating modes using PID control method with fuzzy logic, and results of the test are compared with a classical PID method. In the case of PID control with fuzzy logic, the fuzzy control rules corrects PID parameters each time. Results show that PID control with fuzzy logic has the merits of quick response and reduced overshoot.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.3
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• pp.134-141
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• 2004

Recently, neural network techniques are widely used in adaptive and learning control schemes for production systems. However, in general it takes up a lot of time to learn in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult for the PID gains suitably, lots of researches have been reported with respect of turning schemes of PID gains. A neural network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed neural network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accidents.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.89-91
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• 2004

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult to the PID gains suitably lots of researches have been reported with respect to turning schemes of PID gains. A Neural Network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal is convergence speed progress about applied gain of PID controller using the neural networks.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1094-1097
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• 1999

This paper presents a new PID control scheme based on the feedback of averaged derivatives to realize a noise-free differential control. The PID(Proportional, Integral and Differential) control is still one of the control methods in most wide use. In the paper, the conventional PID control adopting filtering technique is analyzed with new interpretation of filtering function. In order to overcome the drawbacks of the conventional PID control, this paper introduces the feedback of averaged derivatives in the noisy environment, and suggests a new PID control scheme using delay components to realize a noise-free differential control. The proposed PID control yields good performance much similar to the original system response in case of no noises. The proposed control scheme has been tested for the load frequency control of power systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2554-2561
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• 2015

In this paper, we strengthen the advantages of a simple PID controller as a study on the formation control of mobile robots and propose an adaptive PID controller with robust performance at the dynamics characteristics of following robot. Simulation studies show that the adaptive PID controller has better keeping constant distance and angle such as tracking performance of following robot for the formation control than a conventional PID controller. This is the proposed adaptive PID controller to change the gains is found to represent the best performance. This is able to verify that the performance of the proposed adaptive PID controller is excellent.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.124-124
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• 2000

In this paper, The PID controller for stabilization of an inverted pendulum system is proposed. The PR control rule is very common in control systems. It is the basic tool for solving most process control problem. We consider the inverted pendulum system containing two PID controllers. The first controls the angle of the pendulum. The second is used to control the position of the cart. We can show stabilization of the PID controller through simulation of the inverted pendulum system.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.4
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• pp.675-684
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• 2004

The Helicopter system has a non-linearity and complexity. Futhermore, because of absence of its correct mathematical model. it is difficult to control accurately its attitudes for elevation angle and azimuth one. Therefore, we proposed a GA-PID control technique to control these angles efficiently. The proposed GA-PID controller can systematically generate optimal PID parameters by applying GA theory to a helicopter attitude control system. Through the computer simulation, the GA-PID technique shows better attitude control characteristic than traditional PID control technique.