Predictive functional control based on an adaptive fuzzy model of a hybrid semi-batch reactor

被引:49
作者
Dovzan, Dejan [1 ]
Skrjanc, Igor [1 ]
机构
[1] Fac Elect Engn, Ljubljana, Slovenia
关键词
Recursive fuzzy clustering; Recursive fuzzy identification; Clustering; Online recursive identification; Fuzzy predictive functional control; NONLINEAR-SYSTEMS; NEURAL-NETWORKS; FUNCTION APPROXIMATION; INFERENCE SYSTEM; BATCH REACTORS; REAL-TIME; IDENTIFICATION; TEMPERATURE; OPTIMIZATION; ALGORITHM;
D O I
10.1016/j.conengprac.2010.04.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper a new approach to the control of a nonlinear, time-varying process is proposed. It is based on a recursive version of the fuzzy identification method and predictive functional control. First, the recursive fuzzy identification method is derived, after which it is used in connection with fuzzy predictive functional control to construct an adaptive fuzzy predictive functional controller. The adaptive FPFC is then tested on a nonlinear, time-varying, semi-batch reactor process and compared with the standard FPFC, which uses non-adaptive fuzzy model. The simulation results are promising; they indicate that the control of time-varying, nonlinear processes with the FPFC can be improved with the use of an adaptive fuzzy model. An improvement in reference tracking and disturbance rejection can be observed, but the main advantage is the reduced number of switchings between hot and cold water. This is an important improvement in the case of real applications. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:979 / 989
页数:11
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