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end{aligned} (47) Since (V_{k}) is positive definite and (Delta V_{k}) is negative definite, the second Lyapunov theorem guarantees the convergence to zero of the observation error and the observed variables converge to the actual ones.
The control design guarantees the convergence of the tracking error.
The following proposition guarantees the convergence of Algorithm 1.
This constraint guarantees the convergence of the algorithm.
This approximation method is very simple and guarantees the convergence of the approximation.
The scheme guarantees the convergence of the fixed point iteration on the linearized problem.
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Sufficient conditions to guarantee the convergence of ILC are derived.
These methods cannot always guarantee the convergence of approximation series.
Some conditions on the parameters for guaranteeing the convergence of the algorithm are relaxed or removed.
Moreover, we discuss the conditions that, on a theoretical level, guarantee the convergence of this method.
A necessary and sufficient condition guaranteeing the convergence of the algorithm is established.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com