• 제목/요약/키워드: 최적 PID 제어

검색결과 133건 처리시간 0.027초

A study on optimal position control using a microprocessor (마이크로 프로세서를 이용한 최적위치제어에 관한 연구)

  • 양주호;하주식
    • Journal of Advanced Marine Engineering and Technology
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    • 제10권1호
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    • pp.51-64
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    • 1986
  • Recently, being due to development of a small microprocessor, microprocessor have found increasing application as a digital controller in the control system. In this paper, authors analyze theoretically the continuous PID controller of a position control system with servomotor, and program the microprocessor as digital PID controller by an assembly language, and search the optimal parameters of the digital PID controller which make the smallest integral square error criterion for a performance criterion, and take experiment the indicial responses with optimal parameter. The results are following. 1) PD- behavior controller was better than P-behavior controller. 2) The smaller the smapling times of P-behavior controller and PD-behavior controller were, the better the indicial responses of the discrete system were. 3) Using a small microprocessor could replace the traditional continuous PID controller for good control.

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An Optimal Control of Container Crane Using Evolution Strategy (진화전략을 이용한 컨테이너 크레인의 최적제어에 관한 연구)

  • 이영진;이권순
    • Journal of Korean Port Research
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    • 제12권2호
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    • pp.217-224
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    • 1998
  • During the operation of crane system in container yard, the objective is to transport the load to a goal position as quick as possible without rope oscillation. The container crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. Therefore, we developed an optimal controller which has to control the crane system with disturbances. In this paper, we present a design of optima 2-DOF PID controller for the control of gantry crane which has to control swing motion and trolley position. We used evolution strategy(ES) to tune the parameters of 2-DOF PID controller. It was compared with general PID controller. The computer simulations show that the proposed method has better performances than the other method.

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A study on control unit and system for nanoimprint equipment of the optimum conditions. (나노 임프린트 장비 최적 환경을 위한 제어 장비 및 시스템에 관한 연구)

  • Park, Gyeong-Seo;Kim, Woo-Song;Yim, Hong-Jae;Jang, Si-Yeol;Lee, Kee-Sung;Jeong, Jay-Il;Lim, Si-Hyeong;Shin, Dong-Hoon
    • Proceedings of the KSME Conference
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    • 대한기계학회 2008년도 추계학술대회B
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    • pp.2375-2380
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    • 2008
  • Controlling of thermal environment and flow in nanoimprint process chamber is important to ensure high precision levels of products. The purpose of this paper is to build optimal nanoimprint process environment. Because of this, Optimum PI control parameter for precise temperature control has been examined. Also porous medium of ventilation system is simulated for uniform flow in the equipment chamber. The porous medium consists of mesh structure, and is installed to place which flow the influx of the air flows. PID control parameter is based on the data obtained by experiment. And then heating and cooling method which simultaneously operated was used for decreasing an error. In conclude temperature in the equipment chamber was able to control precisely in the range of ${\pm}0.1^{\circ}C$ by the PID control parameter and Deadband.

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Design of an Optimal Controller with Neural Networks for Nonminimum Phase Systems (신경 회로망을 이용한 비최소 위상 시스템의 최적 제어기 설계)

  • 박상봉;박철훈
    • Journal of the Korean Institute of Telematics and Electronics C
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    • 제35C권6호
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    • pp.56-66
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    • 1998
  • This paper investigates a neuro-controller combined in parallel with a conventional linear controller of PID type in order to control nonminimum phase systems more efficiently. The objective is to minimize overall position errors as well as to maintain small undershooting. A costfunction is proposed with two conflict objectives. The neuro-controller is trained off-line with evolutionary programming(EP) in such a way that it becomes optimal by minimizing the given cost function through global evaluation based on desired control performance during the whole training time interval. However, it is not easy to find an optimal solution which satisfies individual objective simultaneously. With the concept of Pareto optimality and EP, we train the proposed controller more effectively and obtain a valuable set of optimal solutions. Simulation results show the efficacy of the proposed controller in a viewpoint of improvement of performance of a step response like fast settling time and small undershoot or overshoot compared with that of a conventional linear controller.

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Design of robust damping controller using flywheel energy storage system (플라이휠 에너지 저장장치를 이용한 강인한 댐핑 제어기 설계)

  • Lee, Jeong-Phil;Han, Snag-Chul;Han, Young-Hee;Hur, Dong-Ryol
    • Proceedings of the KIEE Conference
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.226-227
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    • 2011
  • 본 논문에서는 전력 시스템의 저주파 진동을 효율적으로 억제하기 위하여 기존의 PSS 를 이용하는 방법 대신 FESS를 적용하는 방법을 제시하였다. FESS PID 제어기의 최적 파라미터를 선정하기 위하여 GA를 이용한 방법을 제시하였다. 최적화 파라미터 선정시 사용되는 평가함수를 2가지로 선정하여 선정된 파라미터를 이용하여 FESS PID 제어성능을 평가하였다. 다양한 동작 조건하에 몇 가지 외란이 발생한 경우 비선형 시뮬레이션을 통하여 기존의 PSS를 이용한 방법과 동특성을 비교 고찰하였다.

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Optimal Communication Channel Scheduling for Remote Control of Lead Vehicle in a Platoon (군집 선행차량의 원격제어를 위한 통신 채널의 최적 스케줄링)

  • 황태현;최재원
    • Journal of Institute of Control, Robotics and Systems
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    • 제9권12호
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    • pp.969-976
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    • 2003
  • A remote control strategy for vehicles in Intelligent Vehicle Highway System (IVHS) is considered. An optimal scheduling of a limited communication channel is proposed for lead vehicle control in a platoon. The optimal scheduling problem is to find the optimal communication sequence that minimizes the cost obtained inherently by an optimal control without the communication constraint. In this paper, the PID control law which guarantees the string stability is used for the lead vehicle control. The fact that the PID control law is equivalent to the approximately linear quadratic tracker allows to obtain the performance measure to find an optimal sequence. Simulations are conducted with five maneuvering platoons to evaluate the optimality of the obtained sequence.

An Auto-tuning of PID Controller using Fuzzy Performance Measure and Neural Network for Equipment System (전력설비시스템을 위한 퍼지 평가함수와 신경회로망을 사용한 PID제어기의 자동동조)

  • 이수흠;박현태;이내일
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • 제13권2호
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    • pp.63-70
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    • 1999
  • This paper is proposed a new method to deal with the optimized auto-tuning for the Pill controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. So we can find the parameters of Pill controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of Pill controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of Pill controller is found by Neural-Network Program.rogram.

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Optimum Controller Design of a Water Cooler for Machine Tools Based on the State Space Model (상태공간 모델링에 의한 공작기계용 수냉각기의 최적제어기 설계)

  • Jeong, Seok-Kwon;Kim, Sang-Ho
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • 제23권12호
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    • pp.782-790
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    • 2011
  • Typical temperature control methods of a cooler for machine tools are hot-gas bypass and compressor variable speed control. The hot-gas bypass system has been widely used to control the cooler temperature in many general industrial fields. On the contrary, the compressor variable speed control is focused on special fields such as aerospace and high precision machine tools which need high precision control. The variable speed control system usually has two control variables such as target temperature and superheat. In other words, the variable speed control system is basically multi-input multi-output(MIMO) system. In spite of MIMO system, the proportional integral derivative(PID) feedback control methodology that based on single-input single-output (SISO) system is generally used for designing the variable speed control system. Therefore, it is inevitable to describe transfer functions for dynamic behaviors of every controlled variables and decide the PID gains with tremendous iteration process. Moreover, the designed PID gains do not provide optimum system performances. To solve these problems, high performance controller design method based on a state space model is suggested in this paper. An optimum controller is designed to minimize both control errors and energy inputs. This method was more simple to describe dynamic behaviors and easier to design the cooler controller which is MIMO system.

Implementation of Automated Transfer Crane System using CAN Network (CAN 네트워크를 이용한 자동화 크레인 시스템의 구현)

  • Kim Man-Ho;Ha Kyoung-Nam;Lee Kyung-Chang;Hong Keum-Shik;Lee Suk
    • Journal of Navigation and Port Research
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    • 제29권6호
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    • pp.555-560
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    • 2005
  • Recently, many control systems are replaced with digital control systems in an effort to optimize the overall performance. In order to operate these systems efficiently, the conventional point-to-point connection method must be changed to the signal exchange via a communication network. This paper investigates the technical feasibility of the crane system using CAN protocol which is a part NMEA 2000 by implementing a network-based control system emulating the crane control system.

An Optimized Controller for Nonlinear Plant Based on Neural Network (신경망을 이용한 비선형 플렌트 최적제어에 관한 연구)

  • Min, Lin;XiaoBing, Zhao;Cho, Hyeon-Seob;Park, Wal-Seo
    • Proceedings of the KIEE Conference
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    • 대한전기학회 2002년도 하계학술대회 논문집 D
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    • pp.2490-2492
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    • 2002
  • Design of controller of nonlinear systems is an important part of control research. In this paper, a controller for nonlinear plants using a neural network is presented. The controller is a combination of an approximate PID controller and a neural network controller. The PID controller be used for stabilizing the process and for compensating for possible disturbances, a neural network act as feedforward controller. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system and meets the demands of the system.

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