Neuropredictive control and trajectory generation for slung load systems

Gerardo de La Torre, Eric N. Johnson, Tansel Yucelen

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

This paper presents a neuropredictive trajectory generation architecture for slung load systems. The presented architecture integrates the real-time trajectory generation method with a system uncertainty identifying neural network. It is shown that the effect of system uncertainty on a model predictive control approach can be mitigated by the use of neural networks. A numerical example of an uncertain slung load system is shown to demonstrate the effectiveness of the presented framework.

Original languageEnglish (US)
StatePublished - Sep 16 2013
EventAIAA Infotech at Aerospace (I at A) Conference - Boston, MA, United States
Duration: Aug 19 2013Aug 22 2013

Other

OtherAIAA Infotech at Aerospace (I at A) Conference
CountryUnited States
CityBoston, MA
Period8/19/138/22/13

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

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    de La Torre, G., Johnson, E. N., & Yucelen, T. (2013). Neuropredictive control and trajectory generation for slung load systems. Paper presented at AIAA Infotech at Aerospace (I at A) Conference, Boston, MA, United States.