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This work shows a design procedure which guarantees automatically the global continuity of the law of displacement.
In this contribution we present a joint robust state feedback control/input design procedure which guarantees stability and prescribed closed-loop performance using models identified from experimental data.
Second, the Eidos model was further improved by the addition of the learning/unlearning procedure, which guarantees that only the correct eigenvalues converge.
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We propose a new technique for bottom topography approximation over quadrilateral cells as well as an efficient water surface correction procedure which guarantee the positivity of the computed fluid depth.
This paper describes the adaptive nonlinear control structure composed of approximate linearization and backstepping design procedures which guarantee high quality output regulation in the presence of unknown parameters and unstable internal dynamics.
For the construction, design and operation of nuclear components and systems the appropriate technical codes and standards provide detailed analysis procedures which guarantee a reliable behaviour of the structural components throughout the specified lifetime.
FWER control requires using testing procedures which guarantee that FWER ≤ α with α being the desired significance level.
It is important to perform the complete procedure described above, which guarantees that the final cluster is significant with respect to the present null model (see also Ref. [31]).
The design procedure of observer-based controller is presented, which guarantees the asymptotic stability in the mean square of the resulting closed-loop system with an H∞ performance.
A step-by-step design procedure is presented for the proposed controller, which guarantees stability of the system under worst-case scenarios.
The control synthesis procedure is based on the H∞-optimization, which guarantees robust stability and performance within specified uncertainty bounds by taking into account the effects of unmodeled dynamics, sensor noise, and parametric errors.
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