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An adaptive control allocation algorithm for nonlinear vehicles with parameter uncertainty

Authors: Dong-liang Chen; Guo-ping Liu;

An adaptive control allocation algorithm for nonlinear vehicles with parameter uncertainty

Abstract

In this paper, an adaptive control allocation algorithm is proposed for nonlinear autonomous vehicles. Parameter uncertainty of effectors is considered in the design of allocation algorithm. By designing a nonlinear parameter estimator, it needs not to measure the control moments, i.e., forces and torques. Sensors and corresponding supporting devices to measure and transit the control moments are not needed, thus the overall cost of the control system is reduced, and the hardware system is simplified in implementation. Stability of the overall system is analyzed utilizing the Lyapunov method and sufficient conditions are derived. Digital simulation based on a spacecraft simulator is implemented. The results of the simulation validate the effectiveness of the control scheme.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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