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The H∞ design technique makes the controller robust to unmodeled dynamics, disturbances and approximate errors.
Then stability conditions and conservatism analysis are given, and the approximate errors are proven to be uniformly ultimately bounded (UUB).
The proposed method is robust to approximate errors and disturbances, because it integrates the merits of adaptive fuzzy and the variable structure control.
In the proposed control system, an adaptive recurrent cerebellar model articulation controller (RCMAC) is used to mimic an ideal backstepping control and a robust controller is designed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors.
The proposed method is robust to approximate errors, parameter mismatches and disturbances, because it integrates the merits of the adaptive fuzzy systems and the variable structure control with a sector.
In the proposed control system, an adaptive output recurrent cerebellar model articulation controller (ORCMAC) is used to mimic an ideal backstepping control and a robust controller is designed to attenuate the effects caused by lumped uncertainty term (such as unmodeled dynamics, external disturbances and approximate errors), so that the H∞ tracking performance can be achieved.
Similar(49)
Our approach can be interpreted as approximate error linearization.
This paper presents an approach to the design of nonlinear observers by approximate error linearization.
By optimizing an approximate error function and standard gradient based optimization algorithms, QARNN outputs conditional quantile functions recursively.
Using an analytical least-squares solution to the problem, a simple and approximate error analysis is developed.
For example, those marked CURRENT GUESS ERROR are only working values not to be believed, and APPROXIMATE ERROR means that they have been calculated but there is reason to believe that they may not be accurate.
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CEO of Professional Science Editing for Scientists @ prosciediting.com