Adaptive Control Optimization of Cutting Parameters for High Quality Machining Operations based on Neural Networks and Search Algorithms

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This book chapter presents an Adaptive Control with Optimization (ACO) system for optimising a multi-objective function based on material removal rate, quality loss function related to surface roughness, and cutting-tool life subjected to surface roughness specifications constraint.

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22 p.

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Abellan, J. V.; Romero, F.; Siller, Héctor R.; Estruch, A. & Vila, C. October 1, 2008.

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  • InTech
    Place of Publication: London, United Kingdom

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The UNT College of Engineering strives to educate and train engineers and technologists who have the vision to recognize and solve the problems of society. The college comprises six degree-granting departments of instruction and research.

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Description

This book chapter presents an Adaptive Control with Optimization (ACO) system for optimising a multi-objective function based on material removal rate, quality loss function related to surface roughness, and cutting-tool life subjected to surface roughness specifications constraint.

Physical Description

22 p.

Source

  • Advances in Robotics, Automation and Control, 2008. London, UK: Intech

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  • October 1, 2008

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  • March 15, 2019, 11:51 a.m.

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Abellan, J. V.; Romero, F.; Siller, Héctor R.; Estruch, A. & Vila, C. Adaptive Control Optimization of Cutting Parameters for High Quality Machining Operations based on Neural Networks and Search Algorithms, chapter, October 1, 2008; London, United Kingdom. (https://digital.library.unt.edu/ark:/67531/metadc1459153/: accessed May 26, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.