Optimal Control through Biologically-Inspired Pursuit

Authors:	Shao Cheng, University of Maryland, United States Hristu-Varsakelis Dimitrios, University of Macedonia, Greece
Topic:	2.4 Optimal Control
Session:	Control Applications of Optimization
Keywords:	Co-operative control, Optimization, Agents, Group work, Trajectories

Abstract

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 dynamic systems. A cooperative, pursuit-based algorithm is proposed for finding optimal solutions by iteratively optimizing an initial feasible control. The proposed algorithm requires only short-range, limited interactions between group members, and avoids the need for a ``global map'' of the environment on which the group evolves. The performance of the algorithm is illustrated in a series of numerical experiments.