Suggestions(1)
Exact(4)
Hence, it is expected to that the contour error will converge to zero as well.
The output tracking error will converge to a profile which can be tuned by design parameters and the learning speed is improved if the learning gain is large.
When the modeling errors are available, the indirect backstepping control is proposed, which can guarantee the functional approximation error will converge to a rather small neighborhood of the minimax functional approximation error.
To solve such a challenging problem, a quadratic boundedness (QB) approach is used to design observer in such a way that the state and fault estimation error will converge to the origin (as close as possible) irrespective of the external disturbances.
Similar(54)
Hence, it can be observed that the state estimation error vector will converge in the mean sense provided that the following conditions are fulfilled: 1.
Thus, the error dynamics will converge to zero exponentially by satisfying the strict positive real condition given as equation (8) on the system parameters.
Thus, the error (e(t)) will converge to zero asymptotically, which means that (19) can achieve synchronization.
We also proved through Lyapunov Krasovskii functions that position and force tracking error will asymptotically converge to zero.
It is shown that the internal signals inside closed-loop learning system remain bounded and the output tracking error will asymptotically converge to a profile tunable by some design parameters.
Although the irregular jump error of BLE positioning may exceed 10 m, the ultimate error by fusion positioning will converge into a small value as the time going on.
Hence, the error vector (e(t)) will converge to zero within T̄.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com