Control design for first-order processes: shaping the probability density of the process state

被引：70

作者：

Forbes, MG

Guay, M

Forbes, JF ^{[1
]}

机构：

[1] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2G6, Canada

[2] Queens Univ, Dept Chem Engn, Kingston, ON K7L 3N6, Canada

来源：

JOURNAL OF PROCESS CONTROL | 2004年 / 14卷 / 04期

基金：

加拿大自然科学与工程研究理事会;

关键词：

non-Gaussian processes; non-linear processes; feedback control methods; stationarity; stochastic control; discrete-time processes;

D O I：

10.1016/j.jprocont.2003.07.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

While the long term behaviour of a stationary stochastic process is concisely summarized by the probability density function (PDF), many well-established regulatory control techniques focus only on two quantities derived from the PDF, the mean and variance, as key design targets. This paper presents a technique for the design of control laws that shape all aspects of the PDF of a first-order process. By developing relationships between the moments of the PDF and the coefficients in a control law parameterization, an approximate control law is developed to shape the process PDF as desired. (C) 2003 Elsevier Ltd. All rights reserved.

引用

页码：399 / 410

页数：12

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