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The proposed controller can drive the error dynamics onto the predefined sliding surface in a finite time, and guarantees the property of asymptotical stability without the information of upper bound of uncertainties as well as perturbations.
Then we design an observer to estimate immeasurable states and controller to drive the error between estimated state and virtual desired variables (VDVs) to zero such that the overall control output tracking system has H∞ control performance.
Here, we drive the error down by minimizing the 1-norm of the errors and together with the 1-norm of α for complexity reduction or stabilization.
Although the relative contributions of PCR errors vs. SMRT-sequencing errors were not explored, it is possible that use of a higher-fidelity DNA polymerase during amplification would drive the error frequency even lower.
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We devise stopping criteria to recover the desired order of temporal convergence, and to drive the splitting error below the time-integration error.
Inequality (24) shows that the FOILC scheme (5) is able to drive the tracking error into a bound.
Based on the fractional-order Lyapunov direct method, a controller is designed to drive the synchronization error convergence to zero asymptotically.
Using LMI software, observer gain matrices are computed to satisfy the circle criterion and, hence, to drive the observer error to zero.
The contour error and machining force process reside in the top level of the hierarchy where the goals are to (1) drive the contour error to zero to maximize quality and (2) maintain a constant cutting force to maximize productivity.
That is to say, the proposed backstepping controller is not only to stabilize the flexible robotic manipulator, but also to drive the trajectory tracking error and tip-deflection to converge to zero asymptotically.
In a previous paper (Li et al. (2005)), an iterative learning control (ILC) law, proposed for linear continuous systems with a single time delay, has the ability to drive the output tracking error to zero only after one learning iteration.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com