Abstract
An algorithm based on the Pontryagin's Optimum Principle (POP) is proposed to solve nonlinear receding horizon control problems. Based on a nonlinear state-space plant model, at each time, the corresponding optimal control problem for a finite horizon is solved by imposing the POP conditions that are solved iteratively. These conditions impose a structure on the approximate solution that improves its convergence. The algorithm is illustrated by means of two examples, one concerning motion control and the other HIV-1 infection control.
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