COMPARISON OF LINEAR, NONLINEAR AND NEURAL-NETWORK-BASED ADAPTIVE CONTROLLERS FOR A CLASS OF FED-BATCH FERMENTATION PROCESSES

被引：65
|
作者：
BOSKOVIC, JD
NARENDRA, KS
机构：
[1] YALE UNIV, CTR SYST SCI, DEPT ELECT ENGN, YALE STN, NEW HAVEN, CT 06520 USA
[2] YALE UNIV, DEPT CHEM ENGN, NEW HAVEN, CT 06520 USA
来源：
AUTOMATICA | 1995年 / 31卷 / 06期
基金：
美国国家科学基金会;
关键词：
ADAPTIVE CONTROL; BIO CONTROL; NONLINEAR BIOLOGICAL SYSTEMS; NEURAL NETWORKS;
D O I：
10.1016/0005-1098(94)00139-A
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Five different control strategies for controlling a complex nonlinear and time-varying fermentation process are compared. The main objective of the paper is to determine conditions under which neural-network-based controllers may prove superior to conventional linear and nonlinear adaptive controllers. Extensive computer simulations were performed under identical conditions using the five methods and were evaluated using the same set of criteria. Neural networks are found to be superior when adequate prior information concerning the dynamics of the process is not available and accuracy and robustness are critical issues.
引用
收藏
页码：817 / 840
页数：24
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