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- Author: Leslie Astudillo
- Publisher: Springer
- Year: 2014
- Pages: 77
- ISBN-10: 3319052446
- ISBN-13: 9783319052441
- Format: 15.6 x 23.4 x 0.5 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Chemical Optimization Algorithm for Fuzzy Controller Design (e-book) (used book) | bookbook.eu
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Description
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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- Author: Leslie Astudillo
- Publisher: Springer
- Year: 2014
- Pages: 77
- ISBN-10: 3319052446
- ISBN-13: 9783319052441
- Format: 15.6 x 23.4 x 0.5 cm, minkšti viršeliai
- Language: English 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.
Reviews