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Yasuaki Oishi

Publications and source records attributed to Yasuaki Oishi.

2 recordsLinked to original sources

Infinite-Horizon Sparse Optimal Control: Solution through a Finite-Horizon Subproblem and Its Receding-Horizon Implementation

Sparse optimal control is considered in the infinite horizon. In the literature, sparse control has been considered mostly in a finite horizon for its formulation into a finite-dimensional optimization problem. It is shown in this paper that an optimal solution of the infinite-horizon sparse control problem can be obtained through a solution of some finite-horizon subproblem. This is due to sparsity of the optimal solution in the sense that the optimal control input is constantly equal to zero at its tail. An estimate is given on the horizon length required by this subproblem and its adaptive choice is also discussed. Implementation with a receding-horizon technique is considered and its optimality and sparsity are guaranteed.

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Optimal Sampled-Data Control of a Nonlinear System

Optimal sampled-data control of a nonlinear system is considered with the stable-manifold approach and extensive use of numerical techniques. The idea is to notice the Hamiltonian system associated with the considered optimal control problem and to compute trajectories on its stable manifold. Since the control input accompanied with those trajectories is proved to be optimal, the optimal control law can be obtained through interpolation. The stable-manifold approach was originally proposed for continuous-time optimal control and here it is adapted for sampled-data control based on the works of Navasca. In the case of sampled-data control, the approach requires the state transition of the controlled plant during one sampling period together with its derivatives with respect to the state and the input. Their computation is achieved by numerical techniques. Moreover, a shooting method is proposed for systematic generation of the trajectories and extension is considered for the intersample behavior to be taken into account. The proposed method is applied to tracking control of a wheeled mobile robot. It works successfully with a rather long sampling period.

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