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A sliding-mode controller, which is known to be robust to system uncertainties is designed for fine motion tracking control of the objective lens in vertical direction (focusing).
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The 3D PSS is robust to system parameters changes.
It is proved that the proposed control system is robust to system uncertainties.
It is shown that the proposed system is robust to system uncertainties, environment changes and load variations.
Compared to previously introduced controllers, the proposed control law does not depend on model parameters and thus is robust to system uncertainties.
However, the F ΣΔ DPCA adaptively calculates the optimum gain ratio for motion compensation within each Doppler cell, which is robust to system errors.
A non-linear state feedback controller which is robust to system variations caused by uncertain parameters such as varying payload is developed for the position control of a single-link flexible manipulator fabricated from composite laminates.
Furthermore, the results show that the proposed stabilizer is robust to system changes in the case of small and large disturbances, as well as near the generator stability limit.
Relative to weighted coherence minimization (WCM) and classic CoSaMP, the elaborate performance evaluations show that the FAWC and MFB-CoSaMP can independently or jointly improve accuracy of the CFO-estimation (including coarse CFO-estimation and fine CFO-estimation), and the improvement is robust to system parameters, e.g., sparsity level, number of measurements, etc.
Modelling techniques are needed to manage the high number of combinatorial possibilities arising in multi-drug therapeutic design, and identify synergistic targets that are robust to system uncertainty.
Due to this strategy, system can be robust to illumination variance and classification performance is improved.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com