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

Authors:
Liang Huang;Il Hong Suh;Ajith Abraham
Affiliations:
College of Information & Electronic Engineering, Zhejiang Gongshang University, PR China;Intelligence and Communications for Robots Laboratory, Department of Computer Science and Engineering, College of Engineering, Hanyang University, Seoul, Republic of Korea;Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence (SNIRE), Auburn, WA 98071, USA
Venue:
Information Sciences: an International Journal
Year:
2011

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Abstract

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.