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In this paper, an observer-based fuzzy adaptive controller for nonlinear systems with unknown control gain sign is investigated.
In this paper, a new direct adaptive controller for nonlinear SISO systems with unknown control gain sign is investigated.
A direct adaptive output feedback CMAC (cerebellar model articulation controller) control based on only output measurements is proposed with unknown control gain function for a class of affine nonlinear systems.
Nussbaum function is used to deal with unknown control direction.
Reference [8] developed a fuzzy adaptive control approach for nonlinear systems with unknown control gain sign.
The case of controlling fractional order systems with unknown control input coefficient is also investigated.
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A Nussbaum function is incorporated in the adaptation laws to deal with the unknown control direction (i.e. with the unknown control gain sign).
In this controller, the adaptive fuzzy system is used to approximate the unknown nonlinearities and the Nussbaum function is incorporated to deal with the unknown control direction (i.e. with the unknown control gain sign).
The altitude dynamics is converted into a pure feedback formulation with an unknown control direction, based on which, a novel adaptive neural controller that is quite simpler than the ones derived from back-stepping designs is achieved.
This paper investigates the global adaptive state feedback controller design for a class of feedforward nonlinear systems with completely unknown control direction and unknown growth rate.
Field-scale optimization problems consist of a highly complex reservoir model with many unknown control variables.
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