Abstract
The concepts of the strong second-order sufficient optimality condition and of the linear independence of gradients of active constraints play a crucial role in stability and sensitivity analysis of solutions to finite-dimensional mathematical programming problems. In this paper an attempt is made to use these concepts in stability and sensitivity analysis of solutions to cone-constrained optimization problems in Hilbert spaces. The abstract results are applied to optimal control problems for affine systems subject to state-space constraints.
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