Autor: Soria, J. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Optimization of membership function parameters for fuzzy controllers of an autonomous mobile robot using the flower pollination algorithm
Autorzy:: Carvajal, O. R.
Castillo, O.
Soria, J.
Powiązania:: https://bibliotekanauki.pl/articles/385152.pdf
Data publikacji:: 2018
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: Flower Pollination Algorithm
FPA
membership functions
optimization problems
fuzzy system
algorytm zapylenia kwiatowego
problemy optymalizacyjne
system rozmyty
Opis:: In this work we describe the optimization of a Fuzzy Logic Controller (FLC) for an autonomous mobile robot that needs to follow a desired path. The FLC is for the simulation of its trajectory, the parameters of the membership functions of the FLC had not been previously optimized. We consider in this work with the flower pollination algorithm (FPA) as a method for optimizing the FLC. For this reason, we use the FPA to find the best parameters with the objective of minimizing the error between the trajectory of the robot and the reference. A comparative study of results with different metaheuristics is also presented in this work.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 1; 44-49
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Chemical reaction algorithm for type-2 fuzzy control optimization in mobile robots
Autorzy:: de la O, D.
Castillo, O.
Soria, J.
Powiązania:: https://bibliotekanauki.pl/articles/384488.pdf
Data publikacji:: 2018
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: Chemical Reaction Algorithm
control
fuzzy logic
robotics
Opis:: In this work the optimization process of the tracking and reactive controllers for a mobile robot are presented. The Chemical Reaction Algorithm (CRA) is used to find the optimal parameter values of the membership functions and rules for the reactive and tracking controllers. In this case, we are using five membership functions in each variable of the fuzzy controllers. The main goal of the reactive controller is aimed at providing the robot with the ability to avoid obstacles in its environment. The tests are performed on a benchmark maze problem, in which the goal is not necessarily to leave the maze, but rather that the robot avoids obstacles, in this case the walls, and penalizing for unwanted trajectories, such as cycles. The tracking controller’s goal is for the robot to keep into to a certain path, this in order that the robot can learn to react to unknown environments. The optimization algorithm that was used is based on an abstraction of chemical reactions. To perform the simulation we use the “SimRobot” toolbox, the results of the tests are presented in a detailed fashion, and at the end we are presenting a comparison of results among the CRA, PSO and GA methods.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 3; 10-19
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Optimal design of membership functions of a fuzzy logic controller for an autonomous wheeled mobile robot using ant colony optimization
Autorzy:: Martínez, P.
Castillo, O.
Alanis, A.
Garcia, M.
Soria, J.
Powiązania:: https://bibliotekanauki.pl/articles/384537.pdf
Data publikacji:: 2010
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: fuzzy control
ant colony optimization
autonomous mobile robots
Opis:: In this paper we describe the application of a Simple ACO (S-ACO) as a method of optimization for membership functions' parameters of a fuzzy logic controller (FLC) in order to find the optimal intelligent controller for an Autonomous Wheeled Mobile Robot. Simulation results show that ACO outperforms a GA in the optimization of FLCs for an autonomous mobile robot.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 1; 43-48
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Single spiking neuron multi-objective optimization for pattern classification
Autorzy:: Juarez-Santini, Carlos
Ornelas-Rodriguez, Manuel
Soria-Alcaraz, Jorge Alberto
Rojas-Domínguez, Alfonso
Puga-Soberanes, Hector J.
Espinal, Andrés
Rostro-Gonzalez, Horacio
Powiązania:: https://bibliotekanauki.pl/articles/385022.pdf
Data publikacji:: 2020
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: multi-objective optimization
spiking neuron
pattern classification
Opis:: As neuron models become more plausible, fewer computing units may be required to solve some problems; such as static pattern classification. Herein, this problem is solved by using a single spiking neuron with rate coding scheme. The spiking neuron is trained by a variant of Multi-objective Particle Swarm Optimization algorithm known as OMOPSO. There were carried out two kind of experiments: the first one deals with neuron trained by maximizing the inter distance of mean firing rates among classes and minimizing standard deviation of the intra firing rate of each class; the second one deals with dimension reduction of input vector besides of neuron training. The results of two kind of experiments are statistically analyzed and compared again a Mono-objective optimization version which uses a fitness function as a weighted sum of objectives.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 1; 73-80
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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