Abstract
This text describes the use of a coevolutionary genetic algorithm (CGA) for process control. A CGA combines two artificial life techniques - life-time fitness evaluation (LTFE) and coevolution - to improve the genetic search for a neural network (NN) controlling a given process.
Here, the approach is illustrated and tested on a well-known bioreactor control problem which involves issues of delay, nonlinearity and instability.
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© 1998 Springer-Verlag Wien
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Paredis, J. (1998). Coevolutionary Process Control. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_128
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_128
Publisher Name: Springer, Vienna
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