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Algorithms 2017, 10(3), 85; https://doi.org/10.3390/a10030085

A New Meta-Heuristics of Optimization with Dynamic Adaptation of Parameters Using Type-2 Fuzzy Logic for Trajectory Control of a Mobile Robot

Division of Graduate Studies and Research, Tijuana Institute of Technology, 22414 Tijuana, Mexico
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Received: 4 July 2017 / Revised: 21 July 2017 / Accepted: 22 July 2017 / Published: 26 July 2017
(This article belongs to the Special Issue Extensions to Type-1 Fuzzy Logic: Theory, Algorithms and Applications)
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Abstract

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. View Full-Text
Keywords: fuzzy logic; Type-2; controller; self-defense techniques; herbivores; predator-prey model; Jaccard index fuzzy logic; Type-2; controller; self-defense techniques; herbivores; predator-prey model; Jaccard index
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Caraveo, C.; Valdez, F.; Castillo, O. A New Meta-Heuristics of Optimization with Dynamic Adaptation of Parameters Using Type-2 Fuzzy Logic for Trajectory Control of a Mobile Robot. Algorithms 2017, 10, 85.

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