Dynamic multi-objective optimization based on membrane computing for control of time-varying unstable plants

被引：132

作者：

Huang, Liang

Suh, Il Hong ^{[1
]}

Abraham, Ajith ^{[2
]}

机构：

[1] Hanyang Univ, Intelligence & Commun Robots Lab, Dept Comp Sci & Engn, Coll Engn, Seoul 133791, South Korea

[2] SNIRE, Machine Intelligence Res Labs MIR Labs, Auburn, WA 98071 USA

来源：

INFORMATION SCIENCES | 2011年 / 181卷 / 11期

关键词：

Dynamic multi-objective optimization; Time-varying system; Membrane computing (P systems); Membrane control strategy; GENETIC ALGORITHM; P-SYSTEMS; DESIGN; POWER;

D O I：

10.1016/j.ins.2010.12.015

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Dynamic multi-objective optimization is a current hot topic. This paper discusses several issues that has not been reported in the static multi-objective optimization literature such as the loss of non-dominated solutions, the emergence of the false non-dominated solutions and the necessity for an online decision-making mechanism. Then, a dynamic multi-objective optimization algorithm is developed, which is inspired by membrane computing. A novel membrane control strategy is proposed in this article and is applied to the optimal control of a time-varying unstable plant. Experimental results clearly illustrate that the control strategy based on the dynamic multi-objective optimization algorithm is highly effective with a short rise time and a small overshoot. (C) 2011 Elsevier Inc. All rights reserved.

引用

页码：2370 / 2391

页数：22

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