• Title/Summary/Keyword: multivariable fuzzy

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Fuzzy self-organizing controller for the industrial boiler system (보일러 제어를 위한 퍼지 자기구성 제어기의 설계)

  • 박태홍;배상욱;박귀태;이기상
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.737-741
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    • 1993
  • In this paper, we design the fuzzy logic controller(FLC) for a nonlinear multivariable steam generating unit. Based on the knowledges of operator, the self-organizing controller(SOC) - a kind of FLC - is developed and tested. Both FLC and SOC based on linguistic rules have the advantages of not needing of some exact mathematical model for plant to be controlled. Beside, the SOC modifies the existing control rules by monitoring the control performance. The computer simulations have been carried out for the 200MW steam generating unit to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.

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A Design of Reference Model Following Fuzzy Control System for Boiler-Turbine Equipment (보일러-터빈 설비에 대한 기준모델 추종 퍼지 제어시스템의 설계)

  • 정호성;황창선;황현준
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.11 no.4
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    • pp.82-91
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    • 1997
  • In this paper, a design method of the boiler-turbine control system in the coal fired power plant is proposed. We need to control electric output and drum pressure and water level in drum to guarantee stable operation and save energy for generating electricity and decrease air pollution in the boiler-turbine system. This boiler-turbine control system is composed of reference model part and model following part. The multivariable boiler-turbine system is separated into 3 SISO(Single Input Single Output) systems applying the concept of relative gain matrix. Each 3 reference models for separated boiler-turbine system are composed of 1st order nominal plant and hysteresis integral control system and they make good dy¬namic response with no overshoot and fast rising time. Each fuzzy controller to follow as close as possible to the response of each reference model is designed. The robustness and the good tracking property can be achieved using 5150 fuzzy controllers when there are modeling errors, disturbances and parameter pertur¬bations. The effectiveness of the proposed design method is verified through simulations.

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Robust Real-time Control of Autonomous Mobile Robot Based on Ultrasonic and Infrared sensors (초음파 및 적외선 센서 기반 자율 이동 로봇의 견실한 실시간 제어)

  • Nguyen, Van-Quyet;Han, Sung-Hyun
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.1
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    • pp.145-155
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    • 2010
  • This paper presents a new approach to obstacle avoidance for mobile robot in unknown or partially unknown environments. The method combines two navigation subsystems: low level and high level. The low level subsystem takes part in the control of linear, angular velocities using a multivariable PI controller, and the nonlinear position control. The high level subsystem uses ultrasonic and IR sensors to detect the unknown obstacle include static and dynamic obstacle. This approach provides both obstacle avoidance and target-following behaviors and uses only the local information for decision making for the next action. Also, we propose a new algorithm for the identification and solution of the local minima situation during the robot's traversal using the set of fuzzy rules. The system has been successfully demonstrated by simulations and experiments.

Prognostic Evaluation of Categorical Platelet-based Indices Using Clustering Methods Based on the Monte Carlo Comparison for Hepatocellular Carcinoma

  • Guo, Pi;Shen, Shun-Li;Zhang, Qin;Zeng, Fang-Fang;Zhang, Wang-Jian;Hu, Xiao-Min;Zhang, Ding-Mei;Peng, Bao-Gang;Hao, Yuan-Tao
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.14
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    • pp.5721-5727
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    • 2014
  • Objectives: To evaluate the performance of clustering methods used in the prognostic assessment of categorical clinical data for hepatocellular carcinoma (HCC) patients in China, and establish a predictable prognostic nomogram for clinical decisions. Materials and Methods: A total of 332 newly diagnosed HCC patients treated with hepatic resection during 2006-2009 were enrolled. Patients were regularly followed up at outpatient clinics. Clustering methods including the Average linkage, k-modes, fuzzy k-modes, PAM, CLARA, protocluster, and ROCK were compared by Monte Carlo simulation, and the optimal method was applied to investigate the clustering pattern of the indices including platelet count, platelet/lymphocyte ratio (PLR) and serum aspartate aminotransferase activity/platelet count ratio index (APRI). Then the clustering variable, age group, tumor size, number of tumor and vascular invasion were studied in a multivariable Cox regression model. A prognostic nomogram was constructed for clinical decisions. Results: The ROCK was best in both the overlapping and non-overlapping cases performed to assess the prognostic value of platelet-based indices. Patients with categorical platelet-based indices significantly split across two clusters, and those with high values, had a high risk of HCC recurrence (hazard ratio [HR] 1.42, 95% CI 1.09-1.86; p<0.01). Tumor size, number of tumor and blood vessel invasion were also associated with high risk of HCC recurrence (all p< 0.01). The nomogram well predicted HCC patient survival at 3 and 5 years. Conclusions: A cluster of platelet-based indices combined with other clinical covariates could be used for prognosis evaluation in HCC.