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Inspired by NatureCartesian Genetic Programming for Control Engineering

Inspired by Nature: Cartesian Genetic Programming for Control Engineering [Genetic programming has a proven ability to discover novel solutions to engineering problems. The author has worked with Julian F. Miller, together with some undergraduate and postgraduate students, over the last ten or so years in exploring innovation through evolution, using Cartesian Genetic Programming (CGP). Our co-supervisions and private meetings stimulated many discussions about its application to a specific problem domain: control engineering. Initially, we explored the design of a flight control system for a single rotor helicopter, where the author has considerable theoretical and practical experience. The challenge of taming helicopter dynamics (which are non-linear, highly cross-coupled and unstable) seemed ideally suited to the application of CGP. However, our combined energies drew us towards the more fundamental issues of how best to generalise the problem with the objective of freeing up the innovation process from constrictions imposed by conventional engineering thinking. This chapter provides an outline of our thoughts and hopefully may motivate a reader out there to progress this still embryonic research. The scene is set by considering a ‘simple’ class of problems: the single-input, single-output, linear, time-invariant system.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Inspired by NatureCartesian Genetic Programming for Control Engineering

Part of the Emergence, Complexity and Computation Book Series (volume 28)
Editors: Stepney, Susan; Adamatzky, Andrew
Clarke, Tim
Inspired by Nature — Oct 27, 2017
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Publisher
Springer International Publishing
Copyright
© Springer International Publishing AG 2018
ISBN
978-3-319-67996-9
Pages
157 –173
DOI
10.1007/978-3-319-67997-6_7
Publisher site
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Abstract

[Genetic programming has a proven ability to discover novel solutions to engineering problems. The author has worked with Julian F. Miller, together with some undergraduate and postgraduate students, over the last ten or so years in exploring innovation through evolution, using Cartesian Genetic Programming (CGP). Our co-supervisions and private meetings stimulated many discussions about its application to a specific problem domain: control engineering. Initially, we explored the design of a flight control system for a single rotor helicopter, where the author has considerable theoretical and practical experience. The challenge of taming helicopter dynamics (which are non-linear, highly cross-coupled and unstable) seemed ideally suited to the application of CGP. However, our combined energies drew us towards the more fundamental issues of how best to generalise the problem with the objective of freeing up the innovation process from constrictions imposed by conventional engineering thinking. This chapter provides an outline of our thoughts and hopefully may motivate a reader out there to progress this still embryonic research. The scene is set by considering a ‘simple’ class of problems: the single-input, single-output, linear, time-invariant system.]

Published: Oct 27, 2017

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