A New Control Performance Evaluation Based on LQG Benchmark for the Heating Furnace Temperature Control System

被引:6
|
作者
Li, Haisheng [1 ]
Li, Rongxuan [1 ]
Wu, Feng [1 ]
机构
[1] Hangzhou Dianzi Univ, Automat Coll, Hangzhou 310018, Peoples R China
关键词
linear quadratic Gaussian (LQG) benchmark; fractional order system; FO-PFC control; control performance assessment; CONTROL LOOPS; DESIGN; IDENTIFICATION; DIAGNOSIS;
D O I
10.3390/pr8111428
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Temperature control systems are a series of processes with large time-delay and non-linear characteristics. Research shows that using fractional-order modeling and corresponding control strategies can better control these processes. At the same time, the existing studies for control performance assessment are almost committed to the integer order control systems, and the methods used in few literatures on performance assessment of fractional order systems are also one-sided. This paper applies the linear quadratic Gaussian (LQG) evaluation benchmark to the performance evaluation of fractional-order control systems for the first time, starting with the LQG evaluation benchmark considering the input and output performance. The LQG benchmark can be obtained by the analytical algorithm, which simplifies the complexity of LQG solution. Finally, taking the application of the fractional predictive function control (FO-PFC) controller in the experiment of industrial heating furnace temperature control as an example, the effectiveness of the LQG benchmark is verified.
引用
收藏
页码:1 / 13
页数:13
相关论文
共 50 条
  • [41] Design of Temperature Control System Based on Fuzzy-PWM Control Methods in the Furnace
    Gan Fangcheng
    Huang Haihua
    Liu Baifen
    ISTM/2011: 9TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, 2011, : 148 - 151
  • [42] Automatic control system of external heating vacuum furnace
    Wu, Xingwen
    Chen, Xianyong
    Liao, Chuanshu
    Tian, Dexin
    Kang T'ieh/Iron and Steel (Peking), 1997, 32 (10): : 57 - 59
  • [43] Exploration on the Construction of Experimental System of Heating Furnace Based on Advanced Control Algorithm
    Xia, Gao Yun
    2018 INTERNATIONAL CONFERENCE ON COMPUTER INFORMATION SCIENCE AND APPLICATION TECHNOLOGY, 2019, 1168
  • [44] Predictive fuzzy PID control for temperature model of a heating furnace
    Wang, Yuzhong
    Zou, Hongbo
    Tao, Jili
    Zhang, Ridong
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 4523 - 4527
  • [45] Application of fuzzy control theory to direct-heating furnace control system
    Guan, XZ
    Liu, TN
    Qu, HQ
    PROCEEDINGS OF THE 4TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-4, 2002, : 396 - 399
  • [46] Control of the temperature in a petroleum refinery heating furnace based on a robust modified Smith predictor
    Feliu-Batlle, Vicente
    Rivas-Perez, Raul
    ISA TRANSACTIONS, 2021, 112 : 251 - 270
  • [47] RESEARCH ON TEMPERATURE CONTROL OF HEATING FURNACE WITH INTELLIGENT PROPORTIONAL INTEGRAL DERIVATIVE CONTROL ALGORITHM
    Zheng, Feilong
    Lu, Yundan
    Fu, Shuguang
    THERMAL SCIENCE, 2020, 24 (05): : 3069 - 3077
  • [48] Augmented LQG optimal control of dynamic performance for ETG system
    Zhang, Gui-chen
    2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL IV, PROCEEDINGS, 2009, : 446 - 450
  • [49] MATHEMATICAL MODEL AND CONTROL SYSTEM OF HEATING FURNACE AND HEAT TREATMENT FURNACE.
    Ono, Masahisa
    Yokoi, Tamao
    Makino, Tadashi
    Sumitomo Metals, 1986, 38 (04): : 159 - 166
  • [50] SIMPLE AND RELIABLE FURNACE TEMPERATURE CONTROL SYSTEM
    MORROW, F
    MOORE, A
    JOURNAL OF SCIENTIFIC INSTRUMENTS, 1962, 39 (01): : 34 - &