Abstract
Evolution strategies, based on the natural evolution, are the algorithms to solve the parameter optimization problems numerically. In this paper, a new Evolution Strategy (ES) is proposed to solve optimal control problems. With a view to making a balance between exploration and exploitation, a competing sub-population based arithmetical crossover technique is proposed. The effectiveness of the proposed ES is illustrated by some simulations for the push-cart (a discrete-time optimal control model) control problem.
| Original language | English |
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| Pages | 306-311 |
| Number of pages | 6 |
| Publication status | Published - Jan 1 1997 |
| Externally published | Yes |
| Event | Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA - Monterey, CA, USA Duration: Jul 10 1997 → Jul 11 1997 |
Other
| Other | Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA |
|---|---|
| City | Monterey, CA, USA |
| Period | 7/10/97 → 7/11/97 |
ASJC Scopus subject areas
- Computational Mathematics