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1

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

An analytical insight to investigate the research patterns in the realm of Type-2 fuzzy logic

Vij S., Jain A., Tayal D., Castillo O.

Journal of Automation Mobile Robotics and Intelligent Systems

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2018

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Vol. 12, No. 2

3--32

EN

Fuzzy logic has always been one of the key research areas in the field of computer science as it helps in dealing with the real world vagueness and uncertainty. In recent years, a variant of it, Type-2 Fuzzy Logic has gained enormous popularity for research purposes. In this paper, an analytical insight is provided into the research patterns of Type-2 Fuzzy logic. Web of Science has been used as the data source which consists of Science Citation Index- Expanded (SCI-E), SSCI, A&HCI and ESCI indexed research papers. 600 research papers were extracted from it in the field of Type-2 fuzzy logic from the year 2000 to 2016, which are analyzed both manually and in an automated manner. The performed study is Scientometric in nature and helps in answering research questions like control terms and top authors in this field, the growth pattern in research publications, top funding agencies and countries etc. The major goal of this study is to analyze the research work in type-2 fuzzy logic so as to track the growth of this discipline through the years and envision future trends in this area.

4

A new optimization algorithn based on a paradigm inspired by nature

Astudillo L., Melin P., Castillo O.

Journal of Automation Mobile Robotics and Intelligent Systems

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2011

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Vol. 5, No. 1

95-100

EN

In this paper, we propose a new optimization algorithm for soft computing problems, which is inspired on a nature paradigm: the reaction methods existing on chemistry, and the way the elements combine with each other to form compounds, in other words, quantum chemistry. This paper is the first approach for the proposed method, and it presents the background, main ideas, desired goals and preliminary results in optimization.

5

Optimization of a reactive fuzzy logic controller for a mobile robot using evolutionary algorithms

Meléndez A., Castillo O., Alanis A.

Journal of Automation Mobile Robotics and Intelligent Systems

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2010

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Vol. 4, No. 4

74-77

EN

This paper describes an evolutionary algorithm application for the optimization of a reactive fuzzy controller applied to mobile robot navigation. The evolutionary algorithm optimizes the fuzzy inference system and the position and number of the sensors on the robot, while trying to use the less power possible.

6

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.

7

Novel genetic optimization of membership functions of fuzzy logic for speed control of a direct current motor for hardware applications in FPGAs

Maldonado Y., Castillo O., Melin P.

Journal of Automation Mobile Robotics and Intelligent Systems

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2010

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Vol. 4, No. 4

53-63

EN

This paper proposes a novel method for genetic optimi zation of triangular and trapezoidal membership functions of fuzzy systems, for hardware applications such as the FPGA (Field Programmable Gate Array). This method con sists in taking only certain points of the membership func tions, with the purpose of giving more efficiency to the algorithm. The genetic algorithm was tested in a fuzzy con troller to regulate engine speed of a direct current (DC) motor, using the Xilinx System Generator (XSG) toolbox of Matlab, which simulate VHDL (Very High Description Lang uage) code.

8

Type-1 and Type-2 Fuzzy Inference Systems as Integration Methods in Modular Neural Networks for Multimodal Biometry and its Optimization with Genetic Algorithms

Hidalgo D., Castillo O., Melin P.

Journal of Automation Mobile Robotics and Intelligent Systems

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2008

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Vol. 2, No. 1

59-73

EN

We describe in this paper a comparative study between Fuzzy Inference Systems as methods of integration in modular neural networks for multimodal biometry. These methods of integration are based on techniques of type-1 fuzzy logic and type-2 fuzzy logic. Also, the fuzzy systems are optimized with simple genetic algorithms. First, we considered the use of type-1 fuzzy logic and later the approach with type-2 fuzzy logic. The fuzzy systems were developed using genetic algorithms to handle fuzzy inference systems with different membership functions, like the triangular, trapezoidal and Gaussian; since these algorithms generate the fuzzy systems automatically. Then the response integration of the modular neural network was tested with the optimized fuzzy integration systems. The comparative study of type-1 and type-2 fuzzy inference systems was made to observe the behavior of the two different integration methods for modular neural networks for multimodal biometry.

9

Intelligent Control for a Perturbed Autonomous Wheeled Mobile Robot Using Type-2 Fuzzy Logic and Genetic Algorithms

Martínez R., Castillo O., Aguilar L. T.

Journal of Automation Mobile Robotics and Intelligent Systems

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2008

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Vol. 2, No. 1

12-22

EN

We describe a tracking controller for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on Type-2 Fuzzy Logic Theory and Genetic Algorithms. Computer simulations are presented confirming the performance of the tracking controller and its application to different navigation problems.

10

Soft Computing and Fractal Theory for Intelligent Manufacturing

Castillo O., Melin P.

Journal of Automation Mobile Robotics and Intelligent Systems

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2007

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Vol. 1, No. 1

41-47

EN

We describe in this paper the combination of soft computing techniques and fractal theory for achieving intelligent manufacturing. Soft computing techniques can be used to develop hybrid intelligent systems. Fractal theory can be used to analyze the geometrical complexity of natural and artificial objects. The careful combination of soft computing and fractal theory can provide us with a good mix of intelligent techniques and fractal mathematical tools, which can help in achieving automation of manufacturing processes. We consider in this paper several manufacturing and automation problems that are efficiently solved with the proposed approach.

11

Hybrid intelligent system for pattern recognition

Melin P., Castillo O.

Journal of Automation Mobile Robotics and Intelligent Systems

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2007

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Vol. 1, No. 2

13-19

EN

We describe in this paper a general overview oj the analysis and design of hybrid intelligent systems for pattern recognition applications. Hybrid intelligent systems can be developed by a careful combination of several soft-computing techniques. The combination of soft computing techniques has to take advantage of the capabilities of each technique in solving port of the pattern recognition problem. We review the problems of face, fingerprint and mice recognition and their soiution using hybrid intelligent systems. Recognition rates achieved with the hybrid approaches are comparable with the best approaches known for solving these recognition problems.