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Dynamic multi-objective optimization based on membrane computing for control of time-varying unstable plants |
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| Authors: | Liang Huang Ajith Abraham |
| Affiliation: | a College of Information & Electronic Engineering, Zhejiang Gongshang University, PR China b Intelligence and Communications for Robots Laboratory, Department of Computer Science and Engineering, College of Engineering, Hanyang University, Seoul, Republic of Korea c Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence (SNIRE), Auburn, WA 98071, USA |
| 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. |
| Keywords: | Dynamic multi-objective optimization Time-varying system Membrane computing (P systems) Membrane control strategy |
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