• 제목/요약/키워드: Tuning Algorithm

검색결과 761건 처리시간 0.026초

Tuning of a PID Controller Using Soft Computing Methodologies Applied to Basis Weight Control in Paper Machine

  • Nagaraj, Balakrishnan;Vijayakumar, Ponnusamy
    • 펄프종이기술
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    • 제43권3호
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    • pp.1-10
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    • 2011
  • Proportional.Integral.Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. However PID controller is poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This research comes up with a soft computing approach involving Genetic Algorithm, Evolutionary Programming, and Particle Swarm Optimization and Ant colony optimization. The proposed algorithm is used to tune the PID parameters and its performance has been compared with the conventional methods like Ziegler Nichols and Lambda method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. This research addresses comparison of tuning of the PID controller using soft computing techniques on Machine Direction of basics weight control in pulp and paper industry. Compared to other conventional PID tuning methods, the result shows that better performance can be achieved with the soft computing based tuning method. The ability of the designed controller, in terms of tracking set point, is also compared and simulation results are shown.

Nonlinear self-tuning control incorporating cautious estimation

  • James, D.J.G.;Burnham, K.J.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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    • pp.227-230
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    • 1996
  • The paper highlights the need for cautious least squares estimation when dealing with industrial applications of bilinear self-tuning control and indicates in qualitative terms the benefits of the approach over linear self-tuning control schemes. The cautious least squares algorithm is described and the use of cautious self-tuning in the context of both commissioning and implementation discussed.

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퍼지제어 시스템을 위한 이득동조 방법 (Scaling Factor Tuning Method for Fuzzy Control System)

  • 최한수;김성중
    • 대한전기학회논문지
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    • 제43권5호
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    • pp.819-826
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    • 1994
  • This paper deals with a self-tuning fuzzy controller. The fuzzy controller is constructed with linguistic rules which consist of the fuzzy sets. Each fuzzy set is characterized by a membership function. The tuning fuzzy controller has paramenters that are input/output scaling factors to effect control output. In this paper we propose a tuning method for the scaling factor Computer simulations carried out on first-order and second-order processes will show how the present tuning approach improves the transient and the steady-state characteristics of the overall system.The applicability of the proposed algorithm is certified by computer simulation results.

강인 PID 제어기 설계 (A tuning method for robust PID controller)

  • 윤상준;이상정
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.585-588
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    • 1996
  • The conventional output feedback robust control designs are very useful for systems under parameter perturbation and uncertain disturbance. However these designs are very complicated and not easily implemented for industrial applications. So, this paper proposes a robust PID controller design method via genetic searching algorithm.

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이중 클러스터링 기법을 이용한 퍼지 시스템의 새로운 동정법 (A new identification method of a fuzzy system via double clustering)

  • 김은태;이기철;이희진;박민용
    • 전자공학회논문지C
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    • 제35C권7호
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    • pp.92-100
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    • 1998
  • In this paper, we suggest a new identification method for sugeno-type fuzzy model via new data clustering strategy. The suggested algorithm is much simpelr than the original identification strategy adopted in. The algorithm suggested in this paper is somewhat similar to that of [2] and [6], that is the algorithm suggested in this paper consists of two steps: coarse tuning and fine tuning. In this paper, double clustering strategy is proposed for coarse tunign. Finally, the resutls of computer simulation are given to demonstrate the validity of this algorithm.

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Paper Machine Industrial Analysis on Moisture Control Using BF-PSO Algorithm and Real Time Implementation Setup through Embedded Controller

  • Senthil Kumar, M.;Mahadevan, K.
    • Journal of Electrical Engineering and Technology
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    • 제11권2호
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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.

이중 클러스터링 기법을 이용한 퍼지 시스템의 새로운 동정법 (A New Identification Method of a Fuzzy System via Double Clustering)

  • 김은태;김경욱;이지철;박민기;박민용
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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    • pp.356-359
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    • 1997
  • Recently many studies have been conducted of fuzzy modeling since it can describe a nonlinear system better than the conventional methods. A famous researcher, M. Sugeno, suggested a fuzzy model which superbly describes a nonlinear system. In this paper, we suggest a new identification method for Sugeno-typo fuzzy model. The suggested algorithm is much simpler than the original identification strategy adopted in [1]. The algorithm suggested in this paper is somewhat similar to that of [2]. that is, the algorithm suggested in this paper consists of two consists of two steps: coarse tuning and fine tuning. In this paper, double clustering strategy is proposed for coarse tuning. Finally, the results of computer simulation are given to demonstrate the validity of this algorithm.

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최대 반복 횟수 없이 튜닝에 기반을 둔 HS 최적화 구현 (HS Optimization Implementation Based on Tuning without Maximum Number of Iterations)

  • 이태봉
    • 전기학회논문지P
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    • 제67권3호
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    • pp.131-136
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    • 2018
  • Harmony search (HS) is a relatively recently developed meta-heuristic optimization method imitating the music improvisation process where musicians improvise their instruments' pitches searching for a perfect state of harmony. In the conventional HS algorithm, it is necessary to determine the maximum number of iterations with some algorithm parameters. However, there is no criterion for determining the number of iterations, which is a very difficult problem. To solve this problem, a new method is proposed to perform the algorithm without setting the maximum number of iterations in this paper. The new method allows the algorithm to be performed until the desired tuning is achieved. To do this, a new variable bandwidth is introduced. In addition, the types and probability of harmonies composed of variables is analyzed to help to decide the value of HMCR. The performance of the proposed method is investigated and compared with classical HS. The experiments conducted show that the new method generally outperformed conventional HS when applied to seven benchmark problems.

Design of Fuzzy-Sliding Model Control with the Self Tuning Fuzzy Inference Based on Genetic Algorithm and Its Application

  • Go, Seok-Jo;Lee, Min-Cheol;Park, Min-Kyn
    • Transactions on Control, Automation and Systems Engineering
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    • 제3권1호
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    • pp.58-65
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    • 2001
  • This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that he selected solution become the global optimal solution by optimizing the Akaikes information criterion expressing the quality of the inference rules. The trajectory tracking simulation and experiment of the polishing robot show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding mode controller provides reliable tracking performance during the polishing process.

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반복 최소 자승법을 이용한 전자식 스로틀 바디의 PID 이득 자동 조정 (PID Gain Auto Tuning of ETB by Using RLS)

  • 전찬성;김대상;이장명
    • 로봇학회논문지
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    • 제2권1호
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    • pp.1-8
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    • 2007
  • This paper presents a PID automatic gain-tuning algorithm for the electronic throttle valve which is driven by wire. Since the system characteristics of position control for electronic throttle valve are so complicated that both the real time robustness and the manufacturing cost must be considered for mass production. To resolve this paradox, a kind of algorithm called RLS (Recursive Least Square) is adopted for the control of the ETB (Electronic Throttle Body). Using this algorithm, the PID gains can be adjusted automatically with the estimated system parameters. Furthermore, a pre-filter is supplemented for the sake of the robustness against the friction and loads. From the industrial requests for the system, the design specifications are decided as follows: the settling time should be less than 1sec and the overshoot should be kept below 3%. The results of the experiments based on this approach show that the high robustness can be achieved while the system stability is satisfied steadily. A parameter estimation scheme and a gain-tuning algorithm have been properly combined and utilized in this research and the effectiveness is verified through the real experiments.

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