時相深層展開を用いたモデル予測制御の多重振り子系に対する有効性の検証

抄録

In model predictive control (MPC), the control input at each time point is determined by solving an optimization problem. Being optimization-based, MPC is known for its limited applicability to systems with complex dynamics. This technical gap could be solved by the recently proposed MPC method based on temporal deep unfolding. Deep unfolding is method derived from deep learning, and it is used to solve an optimization problem. Temporal Deep Unfolding-Based MPC’s effectiveness is not yet thoroughly evaluated in the literature. Therefore, in this paper, we evaluate the effectiveness of the method for multilink pendulum systems by simulation.