Cooperative optimal control: broadening the reach of bio-inspiration.
Inspired by the process by which ants gradually optimize their foraging trails, this paper investigates the cooperative solution of a class of free final time, partially constrained final state optimal control problems by a group of dynamical systems. We propose an iterative, pursuit-based algorithm which generalizes previously proposed models and converges to an optimal solution by iteratively optimizing an initial feasible trajectory/control pair. The proposed algorithm requires only short-range, limited interactions between group members, avoids the need for a 'global map' of the environment in which the group evolves, and solves an optimal control problem in 'small' pieces, in a manner which will be made precise. The performance of the algorithm is illustrated in a series of simulations and laboratory experiments.
Shao
Cheng
C
Department of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA. cshao@umd.edu
Hristu-Varsakelis
Dimitrios
D
D000465:Algorithms; D000818:Animals; D001000:Ants; D032701:Biomimetics / Q000379:methods; D003198:Computer Simulation; D003299:Cooperative Behavior; D006126:Group Processes; D008954:Models, Biological; D012919:Social Behavior