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Optimization of membership function parameters for fuzzy controllers of an autonomous mobile robot using the flower pollination algorithm

Carvajal O. R., Castillo O., Soria J.

Journal of Automation Mobile Robotics and Intelligent Systems

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2018

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Vol. 12, No. 1

44--49

EN

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.

2

Chemical reaction algorithm for type-2 fuzzy control optimization in mobile robots

de la O D., Castillo O., Soria J.

Journal of Automation Mobile Robotics and Intelligent Systems

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2018

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Vol. 12, No. 3

10--19

EN

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.

3

Optimal design of membership functions of a fuzzy logic controller for an autonomous wheeled mobile robot using ant colony optimization

Martínez P., Castillo O., Alanis A., Garcia M., Soria J.

Journal of Automation Mobile Robotics and Intelligent Systems

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2010

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Vol. 4, No. 1

43-48

EN

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.