Singular arcs emerge in the solutions of Optimal Control Problems (OCPs) when
the optimal inputs on some finite time intervals cannot be directly obtained
via the optimality conditions. Solving OCPs with singular arcs often requires
tailored treatments, suitable for offline trajectory optimization. This
approach can become increasingly impractical for online closed-loop
implementations, especially for large-scale engineering problems. Recent
development of Integrated Residual Methods (IRM) have indicated their
suitability for handling singular arcs; the convergence of error measures in
IRM automatically suppresses singular arc-induced fluctuations and leads to
non-fluctuating solutions more suitable for practical problems. Through several
examples, we demonstrate the advantages of solving OCPs with singular arcs
using {IRM} under an economic model predictive control framework. In
particular, the following observations are made: (i) IRM does not require
special treatment for singular arcs, (ii) it solves the OCPs reliably with
singular arc fluctuation suppressed, and (iii) the closed-loop results closely
match the analytic optimal solutions.

Este artículo explora los viajes en el tiempo y sus implicaciones.

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