Two-dimensional analysis of an iterative nonlinear optimal control algorithm

Nonlinear optimal control problems usually require solutions using iterative procedures and, hence, they fall naturally in the realm of 2-D systems where the two dimensions are response time horizon and iteration index, respectively. The paper uses this observation to employ 2-D systems theory, in the form of unit memory repetitive process techniques, to investigate optimality, local stability, and global convergence behavior of an algorithm, based on integrated-system optimization and parameter estimation, for solving continuous nonlinear dynamic optimal control problems. It is shown that 2-D systems theory can be usefully applied to analyze the properties of iterative procedures for solving these problems.