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Bio-Inspired Cooperative Optimal Control with Partially-Constrained Final State

dc.contributor.advisorHristu-Varsakelis, Dimitriosen_US
dc.contributor.authorShao, Chengen_US
dc.contributor.authorHristu-Varsakelis, Dimitriosen_US
dc.description.abstractInspired by the process by which ants gradually optimize their foraging trails, this report 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 class of cooperative, pursuit-based algorithms are proposed for finding optimal solutions by iteratively optimizing an initial feasible control. The proposed algorithms require only short-range, limited interactions between group members, avoid the need for a ``global map'' of the environment on which the group evolves, and solve an optimal control problem in ``small'' pieces, in a manner which will be made precise. The performance of the algorithms is illustrated in a series of simulations and laboratory experiments.en_US
dc.format.extent706147 bytes
dc.relation.ispartofseriesISR; TR 2005-76en_US
dc.subjectBiologically-inspired controlen_US
dc.titleBio-Inspired Cooperative Optimal Control with Partially-Constrained Final Stateen_US
dc.typeTechnical Reporten_US

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