Myong-Song Ho

Myong-Song Ho, Kwang-Nam Oh, Chol-Jun Hwang

The hybrid optimal control problem with reach time to a target set is addressed and the continuity and uniqueness of the associated value function is proved. Hybrid systems involves interaction of different types of dynamics: continuous and discrete dynamics. The state ofa continuous system is evolved by an ordinary differential equation until the trajectory hits the predefined jump sets: an autonomous jump set and a controlled jump set . At each jump the trajectory is moved discontinuously to another Euclidean space by a discrete system. We study the hybrid optimal control problem with reach time to a target set, prove the continuity of the associated value function with respect to the initial point under the assumption that is lower semicontinuous on the boundary of a target set, and also characterize it as an unique solution of a quasi-variational inequality in a viscosity sense using the dynamic programming principle.

Myong-Song Ho, Gwang-Hui Ju, Yong-Bom O et al.

We proposed an algorithm for solving Hamilton-Jacobi equation associated to an optimal trajectory problem for a vehicle moving inside the pre-specified domain with the speed depending upon the direction of the motion and current position of the vehicle. The dynamics of the vehicle is defined by an ordinary differential equation, the right hand of which is given by product of control(a time dependent fuction) and a function dependent on trajectory and control. At some unspecified terminal time, the vehicle reaches the boundary of the pre-specified domain and incurs a terminal cost. We also associate the traveling cost with a type of integral to the trajectory followed by vehicle. We are interested in a numerical method for finding a trajectory that minimizes the sum of the traveling cost and terminal cost. We developed an algorithm solving the value function for general trajectory optimization problem. Our algorithm is closely related to the Tsitsiklis's Fast Marching Method and J. A. Sethian's OUM and SLF-LLL[1-4] and is a generalization of them. On the basis of these results, We applied our algorithm to the image processing such as fingerprint verification.