INSTRUMENTAL ENVIRONMENT FOR HYDRO GENERATOR NONLINEAR MODELING AND MULTIPLE-MODEL ADAPTIVE CONTROL

被引:0
|
作者
Ruzhekov, Georgi [1 ]
Puleva, Teofana [1 ]
机构
[1] Tech Univ Sofia, Dept Syst & Control Engn, Sofia, Bulgaria
关键词
hydro turbine; nonlinear modelling; multiple-model adaptive control implementation; PLC; SCADA system;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
An advanced hybrid instrumental environment for hydro generator nonlinear modeling and control is presented in this paper. It consists of a SIMULINK nonlinear plant model and a programmable logical controller (PLC) with proper data acquisition hardware. A multiple-model adaptive control strategy is applied to achieve the desired behavior for control systems with complex nonlinear dynamics. The plant control is determined as a weighted sum of the output signals of particular controllers designed on the predictive error for each models. The multiple-model adaptive control strategy is implemented in software environment of VIPA 313SC controller. A proper SCADA system is developed. The pseudo-parallel control law is designed and applied on the SIMULINK built nonlinear plant model. Laboratory simulations with varying load conditions closed to the practice are carried out in order to explore the system performance.
引用
收藏
页码:383 / 386
页数:4
相关论文
共 50 条
  • [21] Location of Models In Multiple-Model Based Adaptive Control For Improved Performance
    Narendra, Kumpati S.
    Han, Zhuo
    [J]. 2010 AMERICAN CONTROL CONFERENCE, 2010, : 117 - 122
  • [22] Multiple-model adaptive robust dynamic surface control with estimator resetting
    Gan, Minggang
    Chen, Jie
    Li, Zhiping
    [J]. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2015, 29 (08) : 939 - 953
  • [23] Multiple-Model Adaptive Fault-Tolerant Control of a Planetary Lander
    Boskovic, Jovan D.
    Jackson, Joseph A.
    Mehra, Raman K.
    Nguyen, Nhan T.
    [J]. JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2009, 32 (06) : 1812 - 1826
  • [24] Multiple-Model Based Adaptive Control Design for Parametric and Matching Uncertainties
    Tan, Chang
    Tao, Gang
    Qi, Ruiyun
    [J]. 2014 AMERICAN CONTROL CONFERENCE (ACC), 2014,
  • [25] Multiple-model adaptive control using set-valued observers
    Rosa, Paulo
    Silvestre, Carlos
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2014, 24 (16) : 2490 - 2511
  • [26] A Discrete-Time Direct Adaptive Multiple-Model Control Scheme
    Tan Chang
    Tao Gang
    Qi Ruiyun
    [J]. PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE, 2012, : 2997 - 3002
  • [27] Non-fragile multiple-model switching control for nonlinear systems
    Qian, Chengshan
    Hu, Chengzhong
    Jiang, Changsheng
    Wang, Yanqing
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2007, : 31 - +
  • [28] Multiple-model adaptive flight control scheme for accommodation of actuator failures
    Boskovic, JD
    Mehra, RK
    [J]. JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2002, 25 (04) : 712 - 724
  • [29] IMPROVEMENT IN ARTERIAL OXYGEN CONTROL USING MULTIPLE-MODEL ADAPTIVE-CONTROL PROCEDURES
    YU, C
    HE, WG
    SO, JM
    ROY, R
    KAUFMAN, H
    NEWELL, JC
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1987, 34 (08) : 567 - 574
  • [30] IMPROVEMENT IN ARTERIAL OXYGEN CONTROL USING MULTIPLE-MODEL ADAPTIVE CONTROL PROCEDURES.
    Yu, Clement
    He, W.G.
    So, James M.
    Roy, Rob
    Kaufman, Howard
    Newell, Jonathan C.
    [J]. IEEE Transactions on Biomedical Engineering, 1987, BME-34 (08) : 567 - 574