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Stability assessments of the system under parameter scatter are given.
A stability design is then developed to ensure the stability of this nonlinear system under parameter variations.
This paper proposes a viable meta-modeling approach which, based on the approximation of the coefficients of the characteristic polynomial, succeeds in accurately predicting the natural frequencies of the system under parameter variations in presence of veering.
As suggested above, the behavior of the system under parameter variation may provide insight into the elusive functions of Hox transcription factors in the developing limb.
The H∞ filtering theory has been developed for state estimation of nonlinear stochastic signal processing to investigate the noise attenuation problem via minimizing the worst-case effect of noise on the filtering error [ 27, 28] and the H∞ control theory has been developed to robustly stabilize the nonlinear stochastic system under parameter perturbations [ 29, 30].
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We address the problem of output feedback synchronization of certain chaotic systems, under parameter uncertainty.
The results are easily derived from classical control frequency response concepts and provide a simple way of introducing the concepts of control system design under parameter uncertainty to undergraduates.
Therefore, these feedbacks provide extra protections for keeping the system stable under parameter fluctuations [ 22].
Robustness is the ability of maintaining the performance of the controlling system under certain parameter perturbations.
In this work, a novel design approach is proposed to ensure stability and robustness of a nonlinear system under large parameter variations.
Thus, when data is available for the system under study, parameter inference becomes an interesting strategy.
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