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The controller includes robust control term and model compensation term that is developed directly based on the input reference or desired motion trajectory.
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Methods that modify the acoustic model are in general termed (acoustic) model-based or model compensation approaches and comprise inter alia the following sub-categories: so-called model adaptation techniques mostly update the parameters of the acoustic model, i.e., of the hidden Markov models (HMMs), prior to the decoding of a set of observed feature vectors.
The perturbations and model uncertainties effects are canceled out by the injection of a compensation term computed by the application of High-Order Sliding Mode Observers-Identifiers.
Robust control terms are also constructed to effectively attenuate the effect of model compensation errors due to various uncertainties for a theoretically guaranteed transient performance and steady-state tracking accuracy in general.
The control law (31) is then designed such that the common gravity compensation term found in many research works in the literature is eliminated thanks to the contact force virtual model proposed in (28).
A linear current compensation term and an ambient temperature compensation term based on radial basis functions are then applied to the trained Kriging model, leading to the complete discharged capacity-terminal voltage model.
Feature compensation and model compensation robustness methods are studied.
The approaches cited in the litterature can be divided into: free model compensation or model based compensation strategy.
The proposed control terms include a mass flow compensation term, a proportional term, a differential term, and a fuzzy logic term.
The proposed control terms include a nonlinear feedback compensation term, a proportional term, a differential term and a fuzzy logic term.
In addition, an effective method for selecting the compensation term is presented.
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