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Evolutionary neural networks and DNA computing algorithms for dual-axis motion control
- Source :
- Engineering Applications of Artificial Intelligence. 24:1263-1273
- Publication Year :
- 2011
- Publisher :
- Elsevier BV, 2011.
-
Abstract
- A new method is proposed to deal with the dual-axis control of a multi-variables system with two induction motors. Investigation of resolving the cross-coupling problem of dual-axis platform is addressed by a neural net-based decoupling compensator and a sufficient condition ensuring closed-loop stability is derived. An evolutionary algorithm processing the universal seeking capability is proposed for finding the optimal connecting weights of the neural decoupling compensator and the gains of PID controllers. Extensive numerical studies verify the performance and applicability of the proposed design under a variety of operating conditions.
- Subjects :
- Artificial neural network
Computer science
business.industry
Evolutionary algorithm
PID controller
Decoupling (cosmology)
Motion control
law.invention
Artificial Intelligence
Control and Systems Engineering
DNA computing
law
Control theory
Robot
Artificial intelligence
Electrical and Electronic Engineering
business
Induction motor
Decoupling (electronics)
Subjects
Details
- ISSN :
- 09521976
- Volume :
- 24
- Database :
- OpenAIRE
- Journal :
- Engineering Applications of Artificial Intelligence
- Accession number :
- edsair.doi...........03d791254ef6820caa313d06270308f5
- Full Text :
- https://doi.org/10.1016/j.engappai.2011.06.013