On Possible ACD Application for Optimization of Cutting and Assembly in Mechanical Engineering
Application of adaptive critic designs for optimization of real-world processes require a model of the process under optimization or feedback from the real process. For optimization of mechanical manufacturing it is often too expensive and time consuming to use real equipment for the model. However, mathematical models adequately describing real manufacturing processes with realistic noise and interference assumptions may be too difficult to create. We propose to use micro machine tools and micro manipulators as the physical models of real mechanical engineering equipment. They allow us to reduce the cost of experiments and accelerate their speed. We have created prototypes of micro machine tools and work on their use for adaptive critic based optimal control. We describe possible use of adaptive critic designs for optimization of two typical problems of mechanical engineering: shaft cutting and gear fitting on an axle.
E. M. Kussul et al., "On Possible ACD Application for Optimization of Cutting and Assembly in Mechanical Engineering," Neural Netrowks Proceedings, 1998. IEEE World Congress on Computational Intelligence. IEEE / INNS International Joint Conference on Neural Networks '98, vol. 2, pp. 1685-1687, Institute of Electrical and Electronics Engineers (IEEE), Jan 1998.
The definitive version is available at http://dx.doi.org/10.1109/IJCNN.1998.686032
IEEE World Congress on Computational Intelligence (WCCI'98) (1998: May 4-9, Anchorage, AK)
Electrical and Computer Engineering
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© 1998 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.