@misc{10498/40417,
year = {2022},
month = {1},
url = {http://hdl.handle.net/10498/40417},
abstract = {This paper gives some new results on multi-time first-order PDE constrained control optimization problem in the face of data uncertainty (MCOPU). We obtain the robust sufficient optimality conditions for (MCOPU). Further, we construct an unconstrained multi-time control optimization problem (MCOPU) corresponding to (MCOPU) via absolute value penalty function method. Then, we show that the robust optimal solution to the constrained problem and a robust minimizer to the unconstrained problem are equivalent under suitable hypotheses. Moreover, we give some non-trivial examples to validate the results established in this paper},
publisher = {Elsevier},
keywords = {Absolute value penalty function method},
keywords = {Convexity Multi-time control optimization problem},
keywords = {Robust necessary optimality conditions},
keywords = {Robust optimal solution},
title = {Robust penalty function method for an uncertain multi-time control optimization problems},
doi = {https://doi.org/10.1016/j.jmaa.2021.125453},
author = {Jayswal, Anurag and Preeti and Arana Jiménez, Manuel},
}