A new meta-heuristics of optimization with dynamic adaptation of parameters using type-2 fuzzy logic for trajectory control of a mobile robot

被引：28
作者：
Caraveo C. [1 ]
Valdez F. [1 ]
Castillo O. [1 ]
机构：
[1] Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana
来源：
Castillo, Oscar (ocastillo@tectijuana.mx) | 1600年 / MDPI AG卷 / 10期
关键词：
Controller; Fuzzy logic; Herbivores; Jaccard index; Predator-prey model; Self-defense techniques; Type-2;
D O I：
10.3390/a10030085
中图分类号：
学科分类号：
摘要：
Fuzzy logic is a soft computing technique that has been very successful in recent years when it is used as a complement to improve meta-heuristic optimization. In this paper, we present a new variant of the bio-inspired optimization algorithm based on the self-defense mechanisms of plants in the nature. The optimization algorithm proposed in this work is based on the predator-prey model originally presented by Lotka and Volterra, where two populations interact with each other and the objective is to maintain a balance. The system of predator-prey equations use four variables (α, β, λ, δ) and the values of these variables are very important since they are in charge of maintaining a balance between the pair of equations. In this work, we propose the use of Type-2 fuzzy logic for the dynamic adaptation of the variables of the system. This time a fuzzy controller is in charge of finding the optimal values for the model variables, the use of this technique will allow the algorithm to have a higher performance and accuracy in the exploration of the values. © 2017 by the authors.
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