  In the paper, we propose solving optimization problems (OPs) and
understanding the Newton method from the optimal control view. We propose a new
optimization algorithm based on the optimal control problem (OCP). The
algorithm features converging more rapidly than gradient descent, meanwhile, it
is superior to Newton's method because it is not divergent in general and can
be applied in the case of a singular Hessian matrix. These merits are supported
by the convergence analysis for the algorithm in the paper. We also point out
that the convergence rate of the proposed algorithm is inversely proportional
to the magnitude of the control weight matrix and proportional to the control
terminal time inherited from OCP.
