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Chemical Optimization Algorithm for Fuzzy Controller Design [Paperback]

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  • Category: Books (Computers)
  • Author:  Astudillo, Leslie, Melin, Patricia, Castillo, Oscar
  • Author:  Astudillo, Leslie, Melin, Patricia, Castillo, Oscar
  • ISBN-10:  3319052446
  • ISBN-10:  3319052446
  • ISBN-13:  9783319052441
  • ISBN-13:  9783319052441
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  110
  • Pages:  110
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Mar-2014
  • Pub Date:  01-Mar-2014
  • SKU:  3319052446-11-SPRI
  • SKU:  3319052446-11-SPRI
  • Item ID: 100736285
  • List Price: $54.99
  • Seller: ShopSpell
  • Ships in: 5 business days
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  • Delivery by: Jul 03 to Jul 05
  • Notes: Brand New Book. Order Now.

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.

Introduction.-

Theory and Background.-

Chemical Definitions.-

The Proposed Chemical Reaction Algorithm.-

Application Problems.-

Simulation Results.-

Conclusions.

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 tl3‹

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