Chemical Optimization Algorithm for Fuzzy Controller Design

Nonfiction, Science & Nature, Technology, Automation, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Chemical Optimization Algorithm for Fuzzy Controller Design by Leslie Astudillo, Patricia Melin, Oscar Castillo, Springer International Publishing
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Author: Leslie Astudillo, Patricia Melin, Oscar Castillo ISBN: 9783319052458
Publisher: Springer International Publishing Publication: March 13, 2014
Imprint: Springer Language: English
Author: Leslie Astudillo, Patricia Melin, Oscar Castillo
ISBN: 9783319052458
Publisher: Springer International Publishing
Publication: March 13, 2014
Imprint: Springer
Language: English

In this book, a novel optimization method inspired by a paradigm from nature is introduced. The chemical reactions are used as a paradigm to propose an optimization method that simulates these natural processes. The proposed algorithm is described in detail and then a set of typical complex benchmark functions is used to evaluate the performance of the algorithm. Simulation results show that the proposed optimization algorithm can outperform other methods in a set of benchmark functions.

This chemical reaction optimization paradigm is also applied to solve the tracking problem for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application.

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In this book, a novel optimization method inspired by a paradigm from nature is introduced. The chemical reactions are used as a paradigm to propose an optimization method that simulates these natural processes. The proposed algorithm is described in detail and then a set of typical complex benchmark functions is used to evaluate the performance of the algorithm. Simulation results show that the proposed optimization algorithm can outperform other methods in a set of benchmark functions.

This chemical reaction optimization paradigm is also applied to solve the tracking problem for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application.

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