• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.95-103
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• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권2호
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• pp.55-61
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• 2000

In this paper, we proposed a new PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kc, $\tau$I, $\tau$D by the Ziegler-Nichols formula using the ultimate gain and ultimate period from a relay tuning experiment. We get error and error change of plant output correspond to the initial value and new proportion gain(Kc) and integral time($\tau$I) from fuzzy tunner. This fuzzy tuning algorithm for PID controller considerably reduced overshoot and rise time compare to any other PID controller tuning algorithms. In real parametric uncertainty systems, the PID controller with Fuzzy auto-tuning give appreciable improvement in the performance. The significant properties of this algorithm is shown by simulation In this paper, we proposed a new PID algorithm by the fuzzy set theory to improve the performance of the PID controller.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.123-133
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• 2023

Active queue management (AQM) is a leading congestion control system, which can keep smaller queuing delay, less packet loss with better network utilization and throughput by intentionally dropping the packets at the intermediate hubs in TCP/IP (transmission control protocol/Internet protocol) networks. To accelerate the responsiveness of AQM framework, proportional-integral-differential (PID) controllers are utilized. In spite of its simplicity, it can effectively take care of a range of complex problems; however it is a lot complicated to track down optimal PID parameters with conventional procedures. A few new strategies have been grown as of late to adjust the PID controller parameters. Therefore, in this paper, we have developed a Squirrel search based PID controller to dynamically find its controller gain parameters for AQM. The controller gain parameters are decided based on minimizing the integrated-absolute error (IAE) in order to ensure less packet loss, high link utilization and a stable queue length in favor of TCP networks.

• 제어로봇시스템학회논문지
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• 제10권4호
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• pp.317-324
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• 2004

The ink jet printer media advance system is required to be exactly driven to the target position via tracking the reference velocity profile to obtain the high quality print image. A single gain PID controller is not sufficient to fulfill the control objectives, the exact velocity tracking and the accurate positioning, at the same time. A dual PID controller and its switching strategy are presented in this paper to achieve the control objectives. The media advance system is controlled by two separate PID controllers, one of which is for velocity control, and the other is for position control. A PID controller controls the velocity of the media advance system until it reaches the predetermined switching position. When the media advance system passes the predetermined position, the controller is switched to the other PID controller which is more profitable for exact positioning. The switching position is determined by the estimated stop distance. The simulation and experimental results are presented to show the validity and effectiveness of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.362-366
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• 1986

Using simple linear prediction algorithm a design procedure of robust PI and PID controllers for SISO system, usually called 'PID predictor controllers, is developed. The design procedure is able to properly adjust gain margin and phase margin and control coefficients are selected in frequency domain. The performance of the PID predictor controller is superior to that of the normal PID controller in terms of robustness in design and disturbance rejection.

• 전기전자학회논문지
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• 제28권2호
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• pp.136-144
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• 2024

본 논문에서는 실험적 분석을 이용하여 쿼드로터 시스템의 고도제어를 위한 PID제어기를 제안한다. 제안된 제어기가 적용된 시스템의 안정성을 분석하기 위해 Routh-Hurwitz 판별법을 적용한다. 또한 쿼드로터 시스템을 수학적 모델링을 기반으로 MATLAB과 Simulink를 이용하여 k_P, k_I, k_D 각각의 값을 변화시키며 실험의 결과를 정리한다. 정리된 실험의 결과를 바탕으로 PID제어기 각각의 이득값(k_P, k_I, k_D)의 변화가 쿼드로터의 자세제어에 미치는 영향에 대하여 분석하고, 분석한 내용을 바탕으로 제어기 이득값을 튜닝하기 위한 알고리즘을 제시한다. 제안된 알고리즘을 적용한 PID 제어기는 실제 시스템인 AR.Drone에 적용하여 효과를 실험적으로 검증한다.

• 한국항행학회논문지
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• 제17권1호
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• pp.107-114
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• 2013

본 논문에서는 무인항공기 터보제트 엔진의 가속도를 제어하는 제어기를 제안한다. 압축기 회전 속도를 추정하기 위해 고이득 관측기를 사용하고 퍼지 추론 기법과 PID 제어 알고리즘을 적용하는 터보제트 엔진 제어기를 설계한다. 터보제트 엔진의 가 감속 시 서지현상과 flame-out 현상을 방지하기 위해 연료 유량 제어 입력을 퍼지 PID 제어기로 생성한다. 기준 가속도를 설정하고 연료유량 제어를 퍼지추론에 의해 정하도록 한다. 제안된 제어기의 성능을 확인하기 위해 MATLAB을 사용한 컴퓨터 시뮬레이션을 수행하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권6호
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• pp.433-439
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• 2004

The Helicopter Simulator System is non-linear and complex. Futhermore, because of absence of its accurate mathematical model, it is difficult to control accurately its attitudes such as elevation angle and azimuth one. Therefore, we proposed a Hybrid GA-PID WAVENET(Genetic Algorithm Proportional Integral Derivative Wavelet Neural Network)control technique to control efficiently these angles. The proposed Hybrid GA-PID WAVENET is made through the following process. First, the WAVENET fundamental functions are defined. And their dilation and translation values are adjusted by GA to construct the optimal WAVENET controller. Secondly, the proportional, integral, and derivative gain coefficients of PR controller are tuned optimally. Finally, WAVENET controller which has a good transient characteristic and GA-PE controller which has a good steady state characteristic is adequately combined in hybrid type. Through the computer simulations, it is proved that the Hybrid GA-PE WAVENET control technique has a more excellent dynamic response than PID control technique and GA-PID one.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.347-350
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• 1996

With only the classical PID controller applied to control of a DC motor, a good (target) performance characteristic of the controller can be obtained, if all the model parameters of DC motor and operating conditions such as external load torque, disturbance, etc. are exactly known. However, in case when some of system parameters or operating conditions are uncertain or unknown, the fixed PID controller does not guarantee the good performance which is assumed with precisely known system parameters and operating conditions. In view of this and robustness enhancement of DC motor control system, we propose a PID learning controller which consists of a set of learning rules for PID gain tuning and learning of an auxiliary input. The proposed PID learning controller is shown to drive the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one globally asymptotically. Computer simulation results are given to demonstrate the effectiveness of the proposed PID learning controller, thereby showing whose superiority to the conventional fixed PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.229-229
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• 2000

Conventional gain-tuning methods such as Ziegler-Nickels methods, have many disadvantages that optimal control ler gain should be tuned manually. In this paper, modified PID controllers which include self-tuning characteristics are proposed. Proposed controllers automatically tune the PID gains in on-1ine using neural networks. A new learning scheme was proposed for improving learning speed in neural networks and satisfying the real time condition. In this paper, using a nonlinear mapping capability of neural networks, we derive a tuning method of PID controller based on a Back propagation(BP)method of multilayered neural networks. Simulated and experimental results show that the proposed method can give the appropriate parameters of PID controller when it is implemented to DC Motor.