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.
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Notes
- 1.
Here we use the common and convenient Laplace transform notation of a transfer function (\(\bullet (s)\)) to represent the dynamic characteristics of a continuous dynamic system.
- 2.
which would require a significant modification of CGP.
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Clarke, T. (2018). Cartesian Genetic Programming for Control Engineering. In: Stepney, S., Adamatzky, A. (eds) Inspired by Nature. Emergence, Complexity and Computation, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-67997-6_7
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DOI: https://doi.org/10.1007/978-3-319-67997-6_7
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