Simulated response of NN based identification and predictive control of hydro plant

被引:37
|
作者
Kishor, Nand [1 ]
Singh, S. P.
机构
[1] Indian Inst Technol, Alternate Hydro Energy Ctr, Roorkee 247667, Uttar Pradesh, India
[2] Indian Inst Technol, Dept Elect Engn, Roorkee 247667, Uttar Pradesh, India
关键词
hydro plant; identification; predictive control; load disturbances; neural network; simulation;
D O I
10.1016/j.eswa.2005.11.026
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper studies the neural network nonlinear autoregressive with exogenous signal (NNARX) model identification of elastic and inelastic hydro power plant. A nonlinear relationship between the turbine deviated power and random gate position on random load variation and water disturbance is assessed. The identified elastic NNARX hydro plant model is simulated with predictive controller to track a given deviated power as a reference signal. The controller parameters are optimally determined by solving quadratic performance index using well known Levenberg-Marquardt and quasi-Newton algorithm. And it is demonstrated that the deviated power tracks its deviated power target signal accurately over wide rapid-variations in load and water disturbances. (C) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:233 / 244
页数:12
相关论文
共 50 条
  • [21] Model Predictive Control Method of Simulated Moving Bed Chromatographic Separation Process Based on Subspace System Identification
    Yan, Zhen
    Wang, Jie-Sheng
    Wang, Shao-Yan
    Li, Shou-Jiang
    Wang, Dan
    Sun, Wei-Zhen
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2019, 2019
  • [22] THE CONTROL OF HYDRO-ELECTRIC PLANT
    FROST, ACH
    BRITTLEBANK, W
    [J]. PROCEEDINGS OF THE INSTITUTION OF ELECTRICAL ENGINEERS-LONDON, 1951, 98 (63): : 426 - 427
  • [23] THE CONTROL OF HYDRO-ELECTRIC PLANT
    FROST, ACH
    BRITTLEBANK, W
    [J]. PROCEEDINGS OF THE INSTITUTION OF ELECTRICAL ENGINEERS-LONDON, 1951, 98 (111): : 129 - 154
  • [24] State estimation based LQ optimal control in application to hydro plant
    Kishor, Nand
    Singh, S. P.
    Sharma, P. R.
    [J]. 2006 IEEE POWER INDIA CONFERENCE, VOLS 1 AND 2, 2006, : 236 - +
  • [25] A predictive feedback control model using NN and NLMS
    Lee, M
    Im, D
    Park, SS
    Lee, JS
    Wanlee, J
    [J]. KNOWLEDGE-BASED INTELLIGNET INFORMATION AND ENGINEERING SYSTEMS, PT 2, PROCEEDINGS, 2003, 2774 : 822 - 827
  • [26] Fuzzy system identification and predictive control of load system in power plant
    Zhang, HG
    Bien, Z
    [J]. 1998 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AT THE IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE - PROCEEDINGS, VOL 1-2, 1998, : 342 - 347
  • [27] NN-BASED MODEL PREDICTIVE DIRECT SPEED CONTROL OF PMSM DIRECT SYSTEMS
    Guo, Ben
    Xia, Chao
    Han, Jun-Feng
    [J]. PROCEEDINGS OF 2014 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 1, 2014, : 163 - 168
  • [28] Predictive control oriented identification of finite step response model
    Ding B.-C.
    Chen Q.
    Xie Y.-J.
    [J]. Ding, Bao-Cang (baocangding@126.com), 1600, Northeast University (31): : 2030 - 2036
  • [29] A single neuron PID controller for tension control based on RBF NN identification
    School of Quality and Safety Engineering, China Jiliang University, Hang Zhou 310008, China
    [J]. Proc. - IEEE Int. Conf. Comput. Sci. Autom. Eng., CSAE, (178-182):
  • [30] Adaptive Smith Predictive Control Based on Parameter Identification
    Jiang Hongmei
    Cai Dongdong
    Nian Yugui
    Ren Qingchang
    [J]. 2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 2840 - 2843