NDLI: Robust Extended Kalman Filter in Online Tuning Fuzzy Pid Controller for Nonlinear Path following One Unmanned Ground Vehicles

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Robust Extended Kalman Filter in Online Tuning Fuzzy Pid Controller for Nonlinear Path following One Unmanned Ground Vehicles

Content Provider	Semantic Scholar
Author	Javadi, Sh. Tabatabaei, Naser Mahdavi Mortezaei, S. R.
Copyright Year	2018
Abstract	To move an unmanned vehicle from one location to another location, it must be controlled in motion path. The task of the control system is stabilization device and execution commands generated by the navigation system. The most important issue in unmanned vehicle is route planning and tracking the route. One of the most effective in this regard, is traceability route by vehicle. Here traditional PID control and fuzzy control algorithms to combine and offer a response. To identify the control of the Kalman Filter is used to estimate model parameters. The purpose of this article online setting PID fuzzy controller based on Extended Kalman Filter to achieve the best performance control with high stability. Kalman Filter is a powerful mathematical tool for estimating the random noise measurement is used and it will estimate the steady state system. In this article, online setting PID fuzzy controller based on Extended Kalman Filter to achieve better performance and high stability control is used. The purpose of this paper is to design a controller for unmanned aerial vehicles are to be specified path his way through that with the lowest error, variance and time to close and again without any errors and with the least diversion and time to return to its original location.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.iotpe.com/IJTPE/IJTPE-2018/IJTPE-Issue34-Vol10-No1-Mar2018/2-IJTPE-Issue34-Vol10-No1-Mar2018-pp6-15.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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