Hierarchical and distributed optimal control and its application to a motor control model

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In this study, we have applied a primal or dual decomposition technique for large-scale optimization problems into control problems such as formation and consensus problems for multi-agent systems and have proposed control algorithms with hierarchical and distributed structures. Moreover, we have proposed an algorithm in which primal and dual decomposition algorithms are simultaneously performed, so that the stability of the overall system is guaranteed and the computational burden is reduced. Exploiting the analogy between dual decomposition and motor control systems, we have a novel motor control model that contains hierarchical and distributed structures.