Biologically-Inspired Optimal Control via Intermittent Cooperation
| dc.contributor.author | Shao, Cheng | en_US |
| dc.contributor.author | Hristu-Varsakelis, Dimitrios | en_US |
| dc.contributor.department | ISR | en_US |
| dc.contributor.department | CDCSS | en_US |
| dc.date.accessioned | 2007-05-23T10:15:45Z | |
| dc.date.available | 2007-05-23T10:15:45Z | |
| dc.date.issued | 2004 | en_US |
| dc.description.abstract | We investigate the solution of a large class of fixed-final-state optimal control problems by a group of cooperating dynamical systems. We present a pursuit-based algorithm -- inspired by the foraging behavior of ants -- that requires each system-member of the group to solve a finite number of optimization problems as it follows other members of the group from a starting to a final state. Our algorithm, termed "sampled local pursuit", is iterative and leads the group to a locally optimal solution, starting from an initial feasible trajectory. The proposed algorithm is broad in its applicability and generalizes previous results; it requires only short-range sensing and limited interactions between group members, and avoids the need for a "global map" of the environment or manifold on which the group evolves. We include simulations that illustrate the performance of our algorithm. | en_US |
| dc.format.extent | 150078 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1903/6460 | |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | ISR; TR 2004-43 | en_US |
| dc.relation.ispartofseries | CDCSS; TR 2004-4 | en_US |
| dc.subject | Sensor-Actuator Networks | en_US |
| dc.title | Biologically-Inspired Optimal Control via Intermittent Cooperation | en_US |
| dc.type | Technical Report | en_US |
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